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CONTENTS
1.
INTRODUCTION AND SUMMARY ........................................................................................................ 2
1.1
1.2
1.3
2.
THE SCOPE OF THE STUDY .................................................................................................................. 4
2.1
2.2
2.3
2.4
3.
INTRODUCTION ...................................................................................................................................... 4
DEFINITION ............................................................................................................................................ 4
MARKET ANALYSIS ................................................................................................................................ 4
SCOPE OF THE REPORT ........................................................................................................................... 6
IMPACT ON CORPORATE REVENUES AND PROFITS ................................................................... 9
3.1
3.2
3.3
4.
INTRODUCTION ...................................................................................................................................... 2
SUMMARY.............................................................................................................................................. 2
CONCLUSIONS ........................................................................................................................................ 3
INTRODUCTION ...................................................................................................................................... 9
METHODOLOGY ..................................................................................................................................... 9
IMPACT ON REVENUES AND PROFITS .................................................................................................... 12
IMPACT OF COUNTERFEITING ON THE EU ECONOMY ............................................................ 13
4.1
4.2
4.3
4.4
INTRODUCTION .................................................................................................................................... 13
MICROECONOMIC IMPACT .................................................................................................................... 13
METHODOLOGY ................................................................................................................................... 13
RESULTS .............................................................................................................................................. 14
ANNEX 1.
ESTIMATES OF COUNTERFEITING................................................................................. 15
ANNEX 2.
RESPONSES TO OPINION POLL ........................................................................................ 16
ANNEX 3.
MARGINAL PROFITABILITY RATIOS FOR 1996 .......................................................... 17
ANNEX 4.
REVENUE LOSS CALCULATION PROCEDURE ............................................................ 18
ANNEX 5.
RATES OF RETURN ON CAPITAL IN THE BUSINESS SECTOR ................................ 19
ANNEX 6.
ESTIMATING THE ECONOMIC EFFECT ........................................................................ 20
A6.1
A6.2
A6.3
INTRODUCTION .................................................................................................................................... 20
ASSESSING THE ECONOMIC IMPACT OF EU POLICIES AND PROJECTS USING THE ASTRA MODEL ........ 20
MACROECONOMICS SUB-MODULE (MAC) ........................................................................................... 20
ANNEX 7.
CEBR ......................................................................................................................................... 25
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1.
INTRODUCTION AND SUMMARY
1.1
INTRODUCTION
This report describes a study, carried out by the Centre for Economics and Business
Research (CEBR) for the Global Anti-Counterfeiting Group (GACG), of the impact of
counterfeiting on four key sectors in the European Union (EU) and on the EU economies.
It is an extension of a similar study focusing on the UK, which CEBR completed on
behalf of GACG. This study aims to model the impact of counterfeiting within an
economic methodology and to quantify the economic impact of counterfeiting in 4 key
sectors and on the economies of the EU. By describing and quantifying the economic
effects of counterfeiting on the EU, the report addresses some of the questions raised in
the European Commission’s Green Paper on Combating Counterfeiting and Piracy in the
Single Market.
Section 2 outlines the scope of the study, describing the term ‘counterfeiting’, giving a
brief summary of the four industries analysed, and providing an overview of the
economic and social impact of counterfeiting.
Section 3 describes the model and methodology that has been used within this report to
quantify the loss to the affected industries due to counterfeiting. The section then
quantifies the cost from counterfeiting to the clothing and footwear, pharmaceutical, toys
and sports equipment, and perfume and cosmetic industries, measured as loss of revenues
and loss of profits.
Section 4 uses these estimates of the effects on these industries as the inputs to the CEBR
model of the EU economies to calculate the overall loss to the EU economy in terms of
employment and GDP.
1.2
SUMMARY
The study shows that counterfeiting has a serious impact on the revenues, profits and
investment levels of the four sectors studied. Counterfeiting reduces company revenues,
stifles investment and innovation, and retards economic growth. Its final effects on the
general economy are observed directly through job losses and reduced GDP.
1.2.1
Impact on revenues
It shows that counterfeiting in the EU reduces revenues substantially in the affected
industries:
i)
by €7,581 million annually in clothing and footwear;
ii)
by €3,017 million annually in perfumes and cosmetics;
iii)
by €3,731 million annually in toys and sports equipment; and
iv)
by €1,554 million annually in pharmaceuticals.
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1.2.2
Impact on profits
In this study, estimates of profit loss were obtained by applying marginal profitability
ratios to estimates of revenue loss in each sector. This approach differs from that adopted
in the UK study where we applied average profitability ratios. The main costs from
counterfeiting are at the margin (i.e. losses to legitimate producers for every extra
counterfeit unit sold). This means that the marginal profitability of producing counterfeit
goods is a substantial multiple of the average profitability.
In addition the study shows that profits are reduced by significant amounts:
1.2.3
i)
by €1,266 million annually in clothing and footwear;
ii)
by €555 million annually in perfumes and cosmetics;
iii)
by €627 million annually in toys and sports equipment; and
iv)
by €292 million annually in pharmaceuticals.
Impact on the EU economy
The study also shows that counterfeiting has a significant impact on the EU economy
because of the impact on profitability and investment. This negative technology shock
acts to reduce GDP and employment. Our analysis indicates that the macroeconomic
impact on the EU economy of counterfeiting in these 4 industries is to:
1.3
i)
reduce GDP by €8,042 million (at 1995 prices) per annum; and
ii)
reduce EU employment by 17,120 jobs.
CONCLUSIONS
Counterfeiting leads to lost revenue and profits for the sectors concerned. These sectors
also make a significant contribution to the EU economies, through generating jobs and
tax revenues. The study indicates that counterfeiting not only harms these 4 industries
substantially, but also reduces GDP growth and employment in the EU economy.
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2.
THE SCOPE OF THE STUDY
2.1
INTRODUCTION
This section outlines the scope of the study, describing the term ‘counterfeiting’, giving a
brief summary of the four industries analysed, and providing an overview of the impact
of counterfeiting.
2.2
DEFINITION
Counterfeit goods are defined as:
“goods, including the packaging thereof being without authorisation a trade
mark which is identical to the trade mark validly registered in respect of
the same type of goods, or which cannot be distinguished in its essential
aspects from such trade mark, and which thereby infringes the rights of the
holder of the trade mark in question under Community law or the law of
the Member State in which the application for action by the customs
authorities is made
any trade mark symbol (logo, label, sticker, brochure, instructions for use
or guarantee document) whether presented separately or not, in the same
circumstances as the goods referred to in the first indent
packaging materials bearing the trademarks of counterfeit goods, presented
separately in the same circumstances as the goods referred to in the first
indent1.”
2.3
MARKET ANALYSIS
Counterfeiting is a growing problem across the world. Counterfeiters no longer target
luxury goods with developed brands but have also moved into other wider sectors.
However, its impact still remains greatest in these high-end markets. Its prevalence in
certain sectors such as pharmaceutical and toys poses an additional threat to public health
and safety. Less well documented but no less of a problem is counterfeiting within other
industries. This report investigates four other industries where counterfeiting is a
particular problem:
2.3.1
i)
clothing and footwear;
ii)
the pharmaceutical industry;
iii)
toys and sports equipment; and
iv)
the perfume and toiletries industries.
Clothing and footwear
Counterfeiting is a major problem within the clothing and footwear industry. It occurs
especially within the “designer label” market, and the highly lucrative market of high
1
European Commission Council regulation (EC) No 3295/94.
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street fashion. This sector is especially prone to counterfeiting because these products are
relatively easy to emulate. This acts as a strong disincentive for designers to innovate
with the knowledge that within a month a factory in South East Asia is able to copy both
the design and the label and ship the counterfeited goods to markets in the EU.
Clothing and footwear is different from the other industries considered in this study,
because within this market normally the consumer knows that they are buying a fake
item. We estimate that EU clothing and footwear industry generated approximately €238
billion of sales in 1998.
2.3.2
Perfume and toiletries
The EU perfume and toiletries market in 1998 was worth €42 billion. A few large
companies with carefully built up brand names and images dominate the market.
Economies of scale are large, with most of the costs within the industry being the fixed
costs of marketing, design and research and development. These characteristics, similar
to those of the clothing industry, makes the industry susceptible to counterfeiters who
can take advantage of the brand name to sell at premium prices without the fixed costs
faced by legitimate businesses.
2.3.3
Toys and sports equipment
This market is worth approximately €35.5 billion, with the level of counterfeiting in the
industry, it constitutes a significant economic problem.
The toy market is not characterised by company brand names in the classical sense but
by TV and film brands. This strong brand awareness and the intense advertising in the
run-up to Christmas create ideal conditions for profitably counterfeiting branded
products. Moreover, much of the counterfeit toy trade is produced in the same areas as
the legitimate toy trade (South East Asia and China), thus facilitating the production of
counterfeit products.
2.3.4
Pharmaceuticals
The market size is estimated at €26.9 billion in the EU. Counterfeiting of pharmaceutical
products is not only a serious problem for the legitimate pharmaceutical companies in the
form of lost revenues but also for consumers in that the counterfeit products are likely
not to have the medicinal value of the genuine products and may indeed be positively
dangerous.
This problem is becoming endemic in developing countries and Eastern Europe where
within these countries there are well-documented cases of deaths and serious illnesses
from the consumption of fake medicine. Although some of the counterfeit
pharmaceuticals have the same active ingredients as branded products, others contain no
active ingredients and in worse cases may contain harmful, or incorrectly mixed active
ingredients.
A study carried out in 1988 concluded that 51% of counterfeit drugs originated from the
European Community and 46% were sold in developing countries. However for most
countries within the Western Europe and the US, national governments believe that the
level of pharmaceutical counterfeiting is insignificant, presumably because domestic
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sales of counterfeit products are low. Only Italy has reported domestic manufacturing of
counterfeit medicines.
2.4
SCOPE OF THE REPORT
In this study, the main costs of counterfeiting that are considered are set out below.
There are clear costs to:
i)
the companies whose products are counterfeited; and
ii)
those to the economy of the country where the genuine products would otherwise
have been developed and manufactured.
There are other areas where the impact of counterfeiting is more mixed:
i)
the impact to the economies of the countries where the counterfeit products are
manufactured; and
ii)
the costs to consumers of counterfeit products.
In addition to these costs, there are also potential consumer gains from counterfeiting.
2.4.1
Costs to companies whose goods are counterfeited
While there are obvious costs to companies in terms of reduced sales and profits as they
are forced to compete directly against counterfeiters for market share. Other hidden costs
exist which impact on the firm in different ways. There is a loss of future sales from
customer who have been deceived into buying the inferior counterfeit believing it to be
the original. Companies incur significant expense protecting their products, conducting
investigations and litigation.
2.4.2
Costs to the country where legitimate goods would otherwise have been
manufactured
With many counterfeits manufactured outside of the EU and imported, those genuine
articles manufactured in the EU are in direct competition with their counterfeit imports.
The EU as a whole will experience a loss in output and jobs with the loss in demand
from EU consumers of genuine goods. Exports are also affected directly, as companies
have to compete with counterfeit goods at home and abroad.
Counterfeiting leads to reduced tax revenues as corporate tax, indirect and income tax
revenues are reduced. Since very few manufacturers of counterfeit goods will pay any
company/income taxes, this will result in lower tax receipts and hence either a direct loss
in spending or indirect loss through higher taxes for legitimate businesses. The negative
multiplier effect on this lower government spending will result in substantial losses.
The effects of counterfeiting on employment are more pervasive than it might first
appear. There are three main effects on employment. The primary effect is the reduction
in employment as a direct result of a fall in sales and profits. A secondary effect occurs
when firms who supply or service these sectors also reduce employment as demand for
their services declines. And the third effect occurs when induced-demand falls as a
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consequence of the reduction in expenditure by the employees directly employed in the
sector.
Lastly like companies, governments in countries where counterfeits are sold have to
spend increasing amounts of their budgets funding enforcement procedures by the police
and costly judicial cases by the law courts. In the cases where convictions are made
counterfeiting becomes a cost for the prison service. However attempting to assign time
series monetary values to the qualitative statistics is not possible and consequently lies
out of the scope of this document.
2.4.3
Costs to third countries where counterfeit goods are manufactured
If a country manufactures counterfeit products, there is likely to be some gain to the
extent that these counterfeit products replace sales of products made in other countries.
But this potential impact is partly offset by the fact that counterfeiters rarely pay taxes
and often break other laws and regulations in a way that is detrimental to society.
Moreover, if a country gains a reputation for higher than average counterfeit levels,
foreign manufacturers may become reluctant to produce in that country and it may lose
on foreign direct investment. In developing countries this is particularly relevant as they
will lose out on the manufacturing knowledge that is often brought with production.
Where economies such as China and Thailand obtain a reputation for counterfeit goods,
exports of genuine goods may suffer from this slight.
2.4.4
Possible gains from counterfeiting
Whilst clearly there are many losses from counterfeiting there are potentially some gains
that should also be considered. Consumers unable to buy the genuine goods at the full
price may gain utility from buying counterfeit goods at a lower cost, assuming that
quality is sufficiently high. This benefit may potentially be significant, but the difficulty
of calculating a demand curve for the counterfeit industry solely places this calculation
out of the scope of this report.
2.4.5
Social Costs
The impact of counterfeiting on consumers operates through a series of mechanisms:
i)
if the consumer purchases a counterfeit product unwittingly, they are likely
to obtain a product that is of lower quality and perceived value than
expected;
ii)
some counterfeit products (eg pharmaceuticals, toys, car and airplane spares)
pose serious health or safety risks;
iii)
ultimately the consumer suffers from the impact of reduced profits for the
legitimate producers through the producers cutting back on new product
research and development and hence the consumer has available a less
advanced product range;
iv)
counterfeiting is likely to have links to organised crime attracted by the large
profits in this illicit trade; and
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v)
however, there are some minor offsetting consumer gains in some areas (eg
fake clothing in those circumstances where the consumer knows that the
product is counterfeit) where part of the producers’ loss is a gain to the
consumer.
Although these mechanisms operate in different directions, it is likely that the negative
impacts, which are costs to the consumer and society, outweigh the positive impact
where there are consumer gains from counterfeiting.
This study does not consider the impact of counterfeiting on consumers as such although
the macroeconomic assessment in Section 4 picks up some of the impacts of the reduced
expenditure on research and development.
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3.
IMPACT ON CORPORATE REVENUES AND PROFITS
3.1
INTRODUCTION
This section measures the impact of counterfeiting on the revenues and profits of the
companies producing the genuine products. It first describes the methodology used for
the calculation and then sets out the results of the calculation.
3.2
METHODOLOGY
The description of the methodology for estimating revenue and profit losses due to
counterfeiting begins with a simple diagrammatic exposition to fix ideas and then moves
on to a more technical discussion of the estimation procedure.
3.2.1
A Simple Diagrammatic Illustration
The methodology adopted to measure the revenue and profit loss that occurs due to
counterfeiting can be illustrated using a simple industry demand and supply diagram, as
shown in Figure 3.1 below.
The existing situation, where firms in the industry face unfair competition from
counterfeiters, is described by the equilibrium p* and q*.
Figure 3.1
Price
Supply
P**
P*
Q* Q**
Quantity
Demand
D`
To calculate the industry’s revenue loss, an estimate of industry equilibrium is required
under the alternative situation where no counterfeiting occurs.
Clearly the industry demand curve in such a situation will lie further to the right, in a
position such as D` in Figure 3.1.
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The industry’s revenue loss due to counterfeiting is then given by the difference between
total revenue when no counterfeiting occurs, p**q**, and total revenue at present, p*q*.
In practical terms, the estimation of revenue and profit loss for each industry due to
counterfeiting can be done using a five-step procedure.
3.2.2
Estimation of Demand and Supply Slopes
The first step in this procedure concerns the estimation of demand and supply slopes. To
achieve this, we used an econometric model, which was developed as part of the UK
study. The model has the following general specification:
Demand
qt   0  1 pt   2 yt   3 ptA  error
Supply
qt   0  1 pt   2 ct  error
where:
qt
=
sales volume in each industry at time t
pt
=
industry retail price index at time t
yt
=
total personal disposable income at time t
ptA
=
overall retail price index at time t
ct
=
index of costs for each industry at time t
The s and s in each equation are coefficients to be estimated. Of particular interest are
1 and 1 as these represent the model’s estimates of the demand and supply slopes,
respectively. These estimates play a major role in the actual revenue and profit loss
estimation.
3.2.3
Calibration
Given these estimates of the demand and supply slopes, the constants in each equation
are estimated indirectly by calibrating the model to fit the equilibrium values of price and
quantity in each industry for the period 1995-98. This completes the estimation of supply
and demand.
3.2.4
Estimating the “full transfer” size of the demand shift
Using data obtained on the likely scale of counterfeiting in each industry from the ACG
for the UK and Association des Industries de Marque (AIM)2 for the remainder of the
EU, the model was used to estimate directly how much higher total revenue would be
under the alternative scenario where all current counterfeit goods purchases are
transferred to the legitimate sector.
2
See Annex 1 for this data.
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The model, which we employed is data intensive and requires detailed sectoral data. In
the majority of cases the application of the first two stages of this procedure was not
practicable due to lack of data. For these cases we developed an alternative methodology,
which involved calculating the full effect of counterfeiting by applying the estimates of
the size of counterfeiting to the total revenue for each sector. We used the results from
our previous UK study as a guide to the reliability of these results.
Of course, these estimates of the effects of counterfeiting on total revenue represent a
large overestimate in most cases, as counterfeit and non-counterfeit goods are not perfect
substitutes. Put differently, not all individuals who currently purchase counterfeit goods
will transfer their expenditure to non-counterfeit items.
3.2.5
Using survey data to estimate revenue loss
The fourth step of this procedure attempts to take account of any overestimation by using
data from opinion polls3 to scale these total revenue estimates. Respondents were asked
whether they would knowingly purchase a range of counterfeit goods; a high positive
response rate for a good indicates a low degree of substitution between the counterfeit
and non-counterfeit goods. Consequently, the estimated total revenue increase due to the
elimination of counterfeiting would be adjusted downwards to reflect the low degree of
substitution between these goods. Unfortunately, only two countries conducted this type
of survey: Italy and the UK. For the rest of the EU, we used the UK results to scale back
the revenue loss estimates.
3.2.6
Estimating profit loss
The main costs from counterfeiting are at the margin (i.e. losses to legitimate producers
for every extra counterfeit unit sold). This means that the marginal profitability of
producing counterfeit goods is a substantial multiple of the average profitability. For this
study we applied the UK marginal profitability ratios across the EU aggregates to
translate revenue loss directly into estimates of profit loss.4 This measure excludes fixed
costs such as advertising, research and development, and design, which are high in these
sectors.
We opted to apply the UK marginal profitability ratios to the estimated turnover loss for
each EU country because we would expect that the cost structure would be similar across
these industries. Large internationally companies tend to dominate these sectors and their
manufacturing plants have similar economies of scale and cost. We would expect that
there is minimal cost variation across country and it seems a reasonable assumption that
the cost structures are similar across countries.
3
4
See Annex 2 for the results of these polls.
See Annex 3 for the data.
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3.3
IMPACT ON REVENUES AND PROFITS
This section describes the estimated impact on revenues and profits for each of the
industries under consideration using the methodology set out above.
3.3.1
Revenue impact
Table 3.1 provides the estimates of revenue loss due to counterfeiting in the four selected
industries5. As explained above when this procedure was not applicable due to lack of
data we applied an alternative method. The estimation of the loss of revenue involved
calculating the full effect of an elimination of counterfeiting in these industries and then
adjusting these estimates to allow for the fact that counterfeit and non-counterfeit goods
are not perfect substitutes for one another. It is unlikely that the elimination of
counterfeiting will see the full transfer of consumer demand from this market to the
authentic market. The full effect has been adjusted to reflect this and we use national
survey results where appropriate, if not available we use the results from other surveys.
Table 3.1
Estimates of Revenue Loss Due to Counterfeiting
Sector
Percentage of Total
Revenue
Total Loss of Revenue at 1998
Levels (€ millions)
3.2
7,581
7.2
3,017
11.5
3,731
5.8
1,554
Clothing and Footwear
Perfume and Toiletries
Toys and Sports
Pharmaceuticals
In monetary terms, revenues in the clothing and footwear sector experience the largest
loss from counterfeiting. Proportionately, revenues in the toy and sports industry suffer
the greatest impact.
3.3.2
Impact on profits
Estimates of profit loss each year due to counterfeiting are presented in Table 3.2 below.
As explained above these were calculated from total revenue loss using marginal
profitability ratios.
Table 3.2
Estimates of Profit Loss Due to Counterfeiting
Sector
Total Loss of Profit at 1998 Levels
(€ millions)
Clothing and Footwear
Perfume and Toiletries
Toys and Sports
Pharmaceuticals
5
1,266
555
627
292
The procedure for calculating these revenue loss estimates is presented in Annex 4.
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4.
IMPACT OF COUNTERFEITING ON THE EU ECONOMY
4.1
INTRODUCTION
This section extends the analysis of the impact of counterfeiting on companies to
consider the macroeconomic impact on the EU economy.
The section provides estimates of the impact of counterfeiting on investment, GDP and
employment.
4.2
MICROECONOMIC IMPACT
The estimates of the microeconomic impact of counterfeiting consider the four industries
detailed in earlier sections. We estimated a total loss of profits from counterfeiting at
€2,740 million annually in 1998 prices.
To calculate the impact on investment, we used the average rate of return on capital
invested in countries across the EU.6 For the companies to achieve the same rate of return
with the reduced rate of profits, they would have to scale back their investment. The
cumulative impact on capital is €19,558 million.
For the purpose of this macro simulation it is assumed that the impact on investment has
taken place over 5 years. This implies a negative shock of €978 million a quarter over 20
periods.
4.3
METHODOLOGY
The starting point for our macroeconomic analysis is the CEBR’s model of European
economy (EUROMOD2). CEBR has been commissioned by the European Union to
build a macroeconomic model of the European economy for transport policy applications
within the European Union. The model is formulated for each of the 15 EU member
states. Adding together the relevant aggregates for each Member state forms the EU
aggregates.
The model produces a wide range of results of which two are of particular relevance.
These are:
1. The net impact on the economies of the EU – measured by its Gross Domestic
Product – this is the key result for the economic prosperity of EU as a whole;
2. The impact on employment in terms of jobs.
The impact of counterfeiting on the four industries is treated as a negative technology
shock on the EU economies. In the model this operates through investment expenditure –
to simulate this, investment is reduced by €978 million a quarter.
6
See Annex 5 for average rate of return on capital by country.
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4.4
RESULTS
The results summarised in the tables below are shown as the difference between the base
forecasts for the EU economy and the simulated impact of counterfeiting in the 4
industries studied.
Counterfeiting reduces firms’ total revenues and restricts profit. This has implications for
firms’ investment decisions. EUROMOD2 allows us to estimate these effects in terms of
GDP and employment for the European Union.7
Our analysis indicates that the macroeconomic impact on the EU economy of
counterfeiting in these 4 industries is to:
i)
reduce GDP by €8,042 million (at 1995 prices) per annum; and
ii)
reduce EU employment by 17,120 jobs.
EUROMOD2 estimates of the effects of counterfeiting are divided into smaller
geographical zones and by sector.8
Table 4.4.1 Estimates of the Impact on Employment and GDP of Counterfeiting by Zone
Zone
Employment
GDP
(€ 1995 prices)
3,850
2,483
3,940
1,973
3,950
1,589
5,380
1,997
17,120
8,042
Area 1
Area 2
Area 3
Area 4
Total
Table 4.4.2 Estimates of the Impact on Employment and GDP of Counterfeiting by Sector9
Sector
Employment
GDP
(€ 1995 prices)
7,280
3,462
3,520
1,637
4,370
2,001
1,960
937
17,130
8,037
Clothing and Footwear
Perfume and Toiletries
Toys and Sports Goods
Pharmaceuticals
Total
7
Annex 6 provides a greater explanation of the ASTRA model.
Zone 1 includes Germany and Austria; Zone 2 includes France and the Benelux countries; Zone 3 includes
Greece, Italy, Portugal and Spain; and Zone 4 includes Denmark, Finland, Ireland, Sweden and the United
Kingdom.
9 In order to produce estimates of the impact of counterfeiting for individual sectors, it was necessary to
model each sector separately. This gives rise to a small discrepancy between total employment and GDP by
sector and zone.
8
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ANNEX 1.
ESTIMATES OF COUNTERFEITING
Table A1.1 below gives ACG and AIM estimates of the proportion of counterfeit goods
in each of the industries analysed. These estimates are notoriously difficult to calculate
due to the unobserved nature of the problem, and due to their source, they should be
regarded as upper estimates.
Table A1.1
ACG and AIM Estimates of the Proportion of Counterfeit Goods
Sector
ACG/AIM
Clothing and
Footwear
Perfume and
Toiletries
Toys and Sports
11
Pharmaceuticals
6
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ANNEX 2.
RESPONSES TO OPINION POLL
Table A2.1 below contains responses to opinion polls asking the question below or a
variant.
“Which, if any, of the following goods would you knowingly purchase as counterfeit,
assuming you thought the price and quality of the goods was acceptable?”
Table A2.1
Responses to the opinion poll
Product
Proportion of
Interviewees Responding
Positively - UK (%)
Proportion of
Interviewees Responding
Positively - Italy (%)
Clothing and
Footwear
Perfume and
Fragrance
Toys and Sports
52
76
16
38
5
12
Pharmaceutical
5
5
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ANNEX 3.
MARGINAL PROFITABILITY RATIOS FOR 1996
Table A3.1 below contains the marginal profitability ratio for the 4 sectors.
Table A3.1
Marginal Profitability Ratios for 1996
Sector
Marginal Profitability Ratios
(%)
Clothing and
Footwear
Perfume and
Fragrance
Toys and Sports
16.7
Pharmaceutical
18.8
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ANNEX 4.
REVENUE LOSS CALCULATION PROCEDURE
Demand:
q D  a  bp
Supply:
q S  c  dp
Equilibrium requires: q D  q S  q *
 a  bp *  c  dp *
 p* 
ac
bd
and
ad  bc
bd
q* 
To model the revenue lost due to counterfeiting, we take the alternative scenario where there is no
counterfeiting and the firm’s demand curve is further to the right.
New demand:
q ND  a    bp
Equilibrium now occurs where: q ND  q S  q * *
 a    bp * *  c  dp * *
 p** 
ac


bd bd
and
q ** 
ad  bc
d

bd
bd
The effect on total revenue is then found by comparing revenue levels before and after the change, as
follows.
Before:
 a  c  ad  bc 
TR *  p *q *  


 b  d  b  d 
After:
  ad  bc
d 
ac
TR * *  p * *q * *  




bd
 b  d b  d  b  d
Change in revenue:
TR * *  TR * 
In percentage terms:
TR * *  TR *
TR *

1
b  d 2
a    c d  ad  bc 
d

d2


ad  bc a  c a  c ad  bc 
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ANNEX 5.
RATES OF RETURN ON CAPITAL IN THE
BUSINESS SECTOR
The rates of return in the business sector reported in table A5.1 below were extracted
from Table 25 OECD Economic Outlook December 1998.
Table A5.1 Rates of Return on Capital by Country
Country
Rate of Return on Capital (%)
Austria
15.7
Belgium
14.4
Denmark
8.9
Finland
12.9
France
16.4
Germany
15.3
Greece
24.3
Ireland
17.0
Italy
14.6
Luxembourg
14.4
Netherlands
18.9
Portugal
18.2
Spain
18.2
Sweden
11.8
United Kingdom
11.1
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ANNEX 6.
A6.1
ESTIMATING THE ECONOMIC EFFECT
INTRODUCTION
This annex describes the macroeconomic simulation using the ASTRA macroeconomic
model developed for Directorate General VII of the European Commission.
A6.2
ASSESSING THE ECONOMIC IMPACT OF EU POLICIES AND PROJECTS
USING THE ASTRA MODEL
The evaluation of the overall economic impact of counterfeiting has been carried out
using a stand-alone version of the Macroeconomic sub module that the CEBR has
developed for the European Union ASTRA project.
The ASTRA model has been designed as an output of a 4th Framework Research Project
to devise an evaluation and assessment tool for assessing policies and projects10.
The ASTRA model has been developed by CEBR along with the following partners:
IWW, Institut für Wirtschaftspolitik und Wirtschaftsforschung, Universität Karlsruhe
(GER)
TRT, Trasporti e Territorio Srl, Milano (I)
ME&P, Marcial Echenique & Partners Ltd, Cambridge (UK).
ASTRA comprises four key sub-modules. Driving the model is the macroeconomics submodule (MAC) that the CEBR has produced11. This is interlinked with a regional
economics sub-module (REM)12, a transport sub-module (TRA)13 and an environmental
sub-module (ENV)14.
The stand-alone version of the macroeconomic sub-module allows simulations to be
made of shocks to the EU economy. The model’s key relationship is the interaction
between the supply side and the demand side of the economy and the resultant effect that
this generates through inflation and interest rates.
A6.3
MACROECONOMICS SUB-MODULE (MAC)15
This section outlines the CEBR's macro-modelling methodology for the MAC, the model
of the EU macro economy.
The objectives of the model are described in ASTRA Deliverable 1 ‘Review of existing tools’ Chapter 1,
Wolfgang Schade (ed) IWW, 1998.
11 The underlying philosophy of the MAC and a comparison with the macroeconomic models of other
evaluation tools is set out in Chapter 6 of ASTRA Deliverable 1 ‘Review of existing tools’ Wolfgang Schade
(ed) IWW, 1998.
12 Developed by ME&P, Marcial Echenique and Partners Ltd, Cambridge (UK).
13 TRT, Trasporti e Territorio Srl, Milano (I).
14 IWW, Institut für Wirtschaftspolitik und Wirtschaftsforschung, Universität Karlsruhe (GER).
15 This section is an extract from ASTRA Deliverable 3A ‘The ASTRA Systems Dynamics Model Platform’
Wolfgang Schade (ed) IWW, 1999.
10
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A6.3.1
Introduction
The sub-module is based upon the familiar macroeconomic national accounting
framework. It uses national data on the European System of Accounts 1979 basis (ESA
79)16. The sub-module is formulated on the basis of 5 macro regions:
Germany and Austria
France, Belgium, Netherlands and Luxembourg
Italy, Spain, Portugal and Greece
UK, Ireland, Sweden, Denmark and Finland
Rest of the World.
Each of the first 4 macro regions, which include all EU member states, has the equation
structure set out in the equations described in section A6.3.2.
A6.3.2
Internal Structure of the MAC
Inflation and interest rates:
The core identity for the model is real gross domestic product for each region (GDP):
GDP  C + I + G + X – M (eq. 1)
Where:
C = government and household consumption
I = fixed investment plus inventories
X = Exports
M = Imports
This identity therefore gives the aggregate Regional demand for goods and services. The
supply of goods and services in a particular Region is represented by the Potential
Output, modelled by equation [2] below.
YP = YPt-1 . (K/Kt-1)α . (E.Q/Et-1.Qt-1)β . γ
Where:
(eq. 2)
YP = potential output
K = Capital stock
E = Employment
Q = Labour productivity benefits of the policy change to be analysed
α, β, γ = fixed coefficients
16
See European System of Accounts (1995) available from SOEC in Luxembourg or from national statistical offices.
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Potential output depends on the capital stock and the size of the current labour force
taking into account any changes in productivity over time. One such change might result
from the policy changes being analysed (eg business and commuter time savings, if
transport policies are being evaluated). This is treated as increasing labour productivity.
By comparing the supply of goods and services in the form of Potential Output with the
demand for goods and services in the form of GDP expenditure, the rate of inflation in
the Region’s economy can be modelled.
Supply
Demand
Labour Force
Capital Stock
Consumption
Investment
Exports
Imports
Inflation
The rate of inflation is therefore directly dependent upon Potential Output, GDP and the
rate of inflation in the previous period.
P = f (YP, P t-1) (eq. 3)
where:
P = change in prices
YP = potential output
P t-1= changes in prices in the previous period
If demand is outstripping supply then price increases will gradually filter into the
economy and vice-versa.
Inflation is calculated separately for each Region. However in order to take into account
the effects of European Monetary Union a single interest rate is used for the entire EU
area. This reasonably assumes convergence amongst countries outside of the Euro-Zone.
The interest rate is dependent upon the change in inflation, the interest rate in the
previous period and the target rate of inflation.
Int = f (P t-1 , Int t-1, T)
(eq. 4)
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Where
Int = rate of interest
P t-1 = changes in prices in the previous period
T = target rate of inflation
Components of GDP:
Imports grow as a proportion of GDP growth. In other words spending on foreign goods
and services is in line with the general domestic spending trend. The total value of
imports is then split according the source Region using fixed coefficients.
M = f (∆GDP t-4, M t-1)
(eq. 5)
Mi = Ki  M
(eq. 5a)
Where
M = Imports
M i = the imports by region i from the region under consideration.
K = a constant
The total value of a Region’s exports can then be derived from the import figures. For
example Region 1’s exports are the sum of Region 2,3,4 and 5s’ imports from Region 1.
X   M I (eq. 6)
Where
X= exports
M i = the imports by region (i) from the region under consideration.
Investment is a function of the lagged change in GDP. It is also sensitive to the level and
rate of change of interest rates. This reflects the investment decisions of firms based upon
the level of demand and the rate of return.
Inv = f(Invt-1 , ∆GDPt-4 , Int, ∆Intt-1 )
(eq. 7)
Consumption is dependent upon the growth in personal disposable incomes, interest rate
and inflation. Higher interest rates will encourage saving and higher prices will
discourage consumption. Any investment expenditure due to policy changes is
incorporated into the investment equation. Government consumption including the
effects of policy changes is aggregated into the consumption variable. This takes account
of transport taxes, which are calculated through the environmental submodule.
C = f (∆PI, Int, ∆Int, P, ∆P) (eq. 8)
Aggregate personal disposable income grows according to growth in employment and
wage levels.
PDI = f(PDIt-1, ∆Emp, ∆W) (eq. 9)
Where
Emp = Employment
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W = Wage level
Changes in the wage level depend on changes in prices in the previous period,
unemployment, changes in unemployment levels and consumer benefits from the policy
changes.
Wi = f (P t-1, U, U, CB ) (eq. 10)
where:
Wi = change in wages
P t-1 = changes in prices in the previous period
U = unemployment
U = changes in unemployment
CB = Consumer benefits from policy changes
Employment grows relative to the growth in spending in the Region’s economy. It
increases as a proportion of GDP growth and a productivity trend. The model assumes a
2% annual increase in labour productivity.
E = f (GDPt-1, Prod)
Where:
(eq. 11)
E= Employment
Prod = Productivity trend
The unemployment level used in the calculation of the wage level is determined by size
of the labour force – supplied by the REM – minus the employment figure.
Components of Potential Output:
Potential Output is determined by the employment level and capital stock through a
production function. The calculation of Employment has been covered above. The capital
stock grows according to the level of investment taking into account depreciation. It also
takes into account savings in freight costs that are recapitalised and added back into the
capital stock.
K = f (Kt-1, Invt, Z) (eq. 12)
Where
K t-1 = Capital stock in the previous period
Inv t = Investment
Z = External influence on productivity
Region 5 – the rest of the world
Region 5 exists purely in terms of exports and imports. These are derived using the
system of import/export equations described earlier.
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ANNEX 7.
CEBR
This report has been prepared for the Global Anti-Counterfeiting Group by the Centre for
Economics and Business Research (CEBR).
The London-based CEBR is one of Europe’s leading specialist economic consultancies.
Founded in 1993 by Douglas McWilliams, former Chief Economic Adviser to the
Confederation of British Industry, the CEBR has a wide range of clients in the business
and public sector in Europe.
The CEBR maintains and runs models of the World, European, UK and London
economies and is renowned as a leading expert in carrying out economic impact studies.
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