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Measurement of Quality Infrastructure
Ulrich Harmes-Liedtke, Juan José Oteiza Di Matteo
Discussion Paper 5/2011
Physikalisch
Technische
Bundesanstalt
Braunschweig und Berlin
Physikalisch
Technische
Bundesanstalt
Braunschweig und Berlin
Physikalisch-Technische Bundesanstalt
Braunschweig und Berlin
Physikalisch-Technische Bundesanstalt
Braunschweig und Berlin
2
Measurement of Quality Infrastructure
Imprint
Published by: Physikalisch-Technische Bundesanstalt
Bundesallee 100
38116 Braunschweig, Germany
Phone: +49 531 592-82 00
Fax: +49 531 592-82 25
E-mail: marion.stoldt@ptb.de
Web: www.ptb.de/q5
Layout: Jenko Sternberg Design GmbH
(www.jenko-sternberg.de)
Physikalisch-Technische Bundesanstalt
As of: June 2011
Links: www.mesopartner.com
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Ulrich Harmes-Liedtke, Juan José Oteiza Di Matteo
Contents
List of abbreviations and acronyms
PREFACE
EXECUTIVE SUMMARY
1 INTRODUCTION 6
2 MEASUREMENT OF QI 7
2.1 Methodological questions 7
2.1.1 Data heterogeneity 7
2.1.2 The international QI system 7
2.1.3 Available information 9
2.1.4 Sample definition 10
2.1.4.1 Starting point: WTO members 10
2.1.4.2 Clustering criterion within the sample: development perspective 11
2.1.4.3 The best set and the sample selection 12
2.1.4.4 The sample 12
2.2 Measurement of QI components 13
2.2.1 Metrology 13
2.2.2 Accreditation 14
2.2.3 Standardization and Certification 14
2.3 The Indexes 15
2.3.1 The basic measure 15
2.3.2 Measuring in relative terms 16
2.3.3 The relational dimension 18
2.3.4 The composite indicator 19
2.4 The Quality Infrastructure rankings 21
2.5 Limitations and potential improvements 25
3 PERFORMANCE OF QI 26
3.1 An overview 26
3.1.1 Comp et it i v e n e ss 27
3.1.2 GDP per capita 28
3.1.3 Exports 29
3.1.4 Transparency 30
4 FINAL CONCLUSIONS 32
5 BIBLIOGRAPHY 38
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Measurement of Quality Infrastructure
List of abbreviations and acronyms
BIPM International Bureau of Weights and Measures
BMZ Federal Ministry for Economic Cooperation and Development
(Bundesministerium für wirtschaftliche Zusammenarbeit und Entwicklung)
BRIC Brazil, Russia, India and China
CABs Conformity Assessment Bodies
CMC Calibration and Measurement Capabilities
DAC Development Assistance Committee
GlobalGAP Global Partnership for Good Agricultural Practice
IAF International Accreditation Forum
ILAC International Laboratory Accreditation Cooperation
ISO International Organization for Standardization
K&SComp. Total Key and Supplementary Comparisons
LDC Least Developed Countries
Membership Number of Memberships of international QI system
MLA Multilateral Recognition Agreement
MRA Mutual Recognition Agreement
MSTQ Metrology, Standardization, Testing and Quality assurance
NBT Non-tariff Barriers to Trade
NMI National Metrology Institute
NQS National Quality System
ODA Official Development Aid
OECD Organization for Economic Co-operation and Development
POP Country Population
PTB Physikalisch-Technische Bundesanstalt [German Metrology Institute]
QI Quality Infrastructure
SMEs Small and Medium-sized Enterprises
TAB Total Accredited Bodies
TBT Technical Barriers to Trade
Tech.Comm. Total Technical Committees participations
UNCTAD United Nations Conference on Trade and Development
WTO World Trade Organization
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Ulrich Harmes-Liedtke, Juan José Oteiza Di Matteo
PREFACE
This paper is a research initiative of mesopartner, a consultancy firm which has been working for several years in
private sector development and the support of quality infrastructure in developing countries. The elaboration of
this document was supported by the Technical Cooperation of PTB.
The purpose of this paper is to present a methodological proposal for measuring the Quality Infrastructure
(QI) of countries, and promote discussion on this little explored topic. The intention is not to provide
definitive answers on the subject, but to ask questions that encourage the advancement of knowledge in this
area. Specifically, we refer to QI with international recognition in its four areas: Metrology, Standardization,
Certification and Accreditation.
Some benefits that will flow from achieving the aim of this paper are:
a) the possibility of an international comparison between the Quality Infrastructure of countries;
b) help in identifying to whom and where to channel resources from international cooperation
with the aim of improving that infrastructure and;
c) the promotion of discussion between technicians and academics to enable measurement methodologies
to move toward more virtuous forms than those raised here.
The authors are grateful for the valuable contributions and comments made by several colleagues from the
Technical Cooperation of PTB and consultant colleagues, especially Dieter Schwohnke, Marion Stoldt, Alexis
Valqui, Manfred Kindler and Clemens Sanetra. Their practical experience in supporting QI throughout the
developing world helped to provide a better understanding of the quantitative research results.
We hope this document will serve to encourage further discussion on the best methodologies to measure and
compare QI and its performance internationally. Comments and critiques are welcome and appreciated.
EXECUTIVE SUMMARY
This paper gives an overview of the institutional framework of Quality Infrastructure (QI) with an international
perspective. It develops a composite indicator to measure and compare the development and the performance
of QI in a selection of 53 different nations worldwide. The indicator uses freely available data: Total Accredited
Bodies of the National Quality System, number of Calibration and Measurement Capabilities certifications,
ISO 9001 per country, key and supplementary comparisons carried out by National Metrology Institutes,
participation in Technical Committees of International Standards Organization and membership of international
organizations backing the credibility of the national QI.
The paper analyzes the correlation between the Quality Infrastructure development of a nation and key
economic performance indicators like GDP (per capita), Exports and Global Competitiveness and Transparency.
Positive correlations were found for all four variables, supporting the expected relationship between QI
development and economic performance indicators.
The authors understand the proposed QI measurement indicator as just the first step in a more solid comparison
between different national systems. The pragmatic approach of using only freely available data also makes
the results dependent on sometimes unsatisfactory data quality. In addition, relevant qualitative differences
between identical quantitative data were not analyzed in detail. Because of these limitations, the results of
rankings should be interpreted carefully. Nevertheless, the quantitative comparison of national QI could be part
of a broader Benchmarking and collective learning process to improve the development and performance of
Quality Infrastructure bodies in the developing world.
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Measurement of Quality Infrastructure
1 INTRODUCTION
The Physikalisch-Technische Bundesanstalt (PTB) is the National Metrology Institute of Germany and measures
with the highest accuracy and reliability. It is part of a broader system of Quality Infrastructure which includes
metrology, standards, testing laboratories, certification and accreditation bodies and quality management at the
firm and organizational level itself.
The International Technical Cooperation of the PTB is engaged to promote Quality Infrastructure in developing
countries. On behalf of the German Ministry of Economic Cooperation and Development (German acronym
BMZ), it uses its technical expertise and excellence to support peer institutions and other QI related
organizations in developing their own national QI.
Surprisingly, even though measurement is the core competence of the PTB, there are no clear indicators and
tools to measure QI itself. Obviously the measurement of a complex institutional arrangement is not an easy
task. It involves a multitude of different organizations, institutional regulations and, last but not least, humans,
and thus also entails measuring social phenomena (i.e. trust, confidence or quality culture), which are not
measurable with technical instruments. In addition, each economy has different requirements for the necessary
QI, so evaluation of the level of development of a QI will depend on the specific needs of the countries.
Why is it important to measure QI?
Generally, what can be measured can be understood, controlled, predicted and changed.
In the case of entities responsible for supporting QI in developing countries, we may mention the following
arguments to support the need for QI measurement. Measurements of national QI
• help to better understand the system dynamics of QI and improve interventions
• make possible the identification of best practices where QI develops and contributes to innovation,
competitiveness and development
• could be a basis for a Benchmarking system which encourages improvement and mutual learning
• should be part of a broader monitoring and evaluation system which includes the final objective of the
Technical Cooperation of PTB and other donors.
This paper uses the key components of QI (mainly Metrology; Standards; Certifications and Accreditation) to
measure national QI. For each component we analyze statistical data at the country level. The selection of
the data sources is pragmatic, using only data from international QI institutions which are freely available on
the Internet. Based on the data of the different components, we create a joint indicator to measure QI at the
national level.
In the second part of the paper we analyze the correlation between QI measures and economic performance
measures (exportation, innovation, competitiveness, income). This helps us to see the efficiency of a QI system.
Our hypothesis is that a country with a well-developed QI is also economically successful and, inversely,
countries lagging behind in QI are also economically less advantaged. For successful performance it is not
sufficient to understand the evolution of GDP per capita; export performance, the level of competitiveness and
transparency must be understood as well.
This study does not explain the causalities. The question of whether the development of a national QI causes
economic progress or else economic progress helps to build a national QI is not part of the analysis. This and
other issues will require further research and we outline some suggestions in the final chapter.
Measure what is measurable, and make measurable what is not so.
Galileo Galilei If you want it, measure it. If you can't measure it, forget it.
Peter Drucker
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Ulrich Harmes-Liedtke, Juan José Oteiza Di Matteo
2 MEASUREMENT OF QI
2.1 Methodological questions
2.1.1 Data heterogeneity
When browsing websites of local accrediting and certification bodies, and NMIs, we found that the quality of
information and its availability is quite heterogeneous. Examples of this include: the latest available data relate to
different points in time in many cases, data sources are not necessarily primary or freely accessed, and the information
they provide is not equally reliable. Furthermore, the information on websites is presented in very different ways which
makes data collection for comparison purposes difficult. Initially, this significantly weakened the aim of this paper.
To reduce the impact of these problems, we decided to analyze only countries which are embedded in the
international QI and trade system. Thus, the observed components of the national quality system would
comply with certain international protocols that tend to homogenize the quality of their products (certification,
standards, accreditations, measurements and calibrations certificates), improving information comparability.
We say that a country is integrated into the international quality system when it is a full member of at least
one of the international accreditation, certification, standardization or metrology bodies with recognition
worldwide. But we must bear in mind that the requirements for membership in each other's bodies are
different, and only a few countries belong to all international quality system organizations. Hence, if we
select countries according to membership, the sets are quite variable in number and members. A detailed
analysis of how different groups are formed can be made from the table attached in the Appendix. In any
case, the requirements imposed on bodies with regard to membership give a minimum guarantee in terms of
transparency, accreditation and certification procedures, and consistency in the information they provide.
2.1.2 The international QI system
A brief introduction to some relevant international bodies considered in this paper was taken from their websites
and is shown below.
Accreditation
The International Accreditation Forum, Inc. (IAF) is the world association of Conformity Assessment
Accreditation Bodies and other bodies interested in conformity assessment in the fields of management systems,
products, services, personnel and other similar programmes of conformity assessment. Accreditation Body
Membership of IAF is open to Bodies conducting and administering programs by which they accredit bodies
that declare their common intention to join the IAF Multilateral Recognition Agreement (MLA) recognizing the
equivalence of other members' accreditations to their own.
The International Laboratory Accreditation Cooperation (ILAC) is an international cooperation of laboratory and
inspection accreditation bodies formed more than 30 years ago to help remove technical barriers to trade. Accreditation
bodies that meet the requirements for Associates and have also been accepted as signatories to the ILAC Mutual
Recognition Arrangement (MRA) become Full Members. Associates of ILAC must: i) operate accreditation schemes for
testing laboratories, calibration laboratories, inspection bodies, and/or other services as decided from time to time by
the ILAC General Assembly; ii) can provide evidence that they are operational and committed to complying with: (a) the
requirements set out in relevant standards established by appropriate international standards writing bodies such as the
International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC) and ILAC
application documents; and (b) the obligations of the ILAC Mutual Recognition Arrangement; iii) are recognized in their
economy as offering an accreditation service. The cooperation between the two organizations is intense. In fact, they
currently hold joint assemblies and there is the prospect of the two agencies merging in the future.
8
Measurement of Quality Infrastructure
Standardization
The International Electrotechnical Commission (IEC) is the world‘s leading organization that prepares
and publishes International Standards for all electrical, electronic and related technologies collectively known
as „electrotechnology“. Full Membership allows countries to participate fully in international standardization
activities. They are National Committees which represent their nation‘s electrotechnical interests in IEC
management and standardization work.
International Communication Union (ITU) is the leading United Nations agency for information and
communication technology issues, and the global focal point for governments and the private sector in
developing networks and services. Membership of ITU is open to governments, which may join the Union as
Member States.
The International Organization for Standardization (ISO) is the world‘s largest developer and publisher
of international standards. A member body of ISO is the national body „most representative of standardization
in its country“. Only one such body for each country is accepted for membership of ISO. Member bodies are
entitled to participate and exercise full voting rights on any technical committee and policy committee of ISO.
In this case too, the cooperation between organizations of standardization is intense. One example is the Joint
Technical Committee of the ISO and IEC, which deals with all matters related to information technology.
Certification
The emission of certificates based on standards is mainly a private business. The competence and impartiality
of the certification bodies requires a conformity assessment by ISO/IEC 17021, which is carried out by national
accreditation bodies.
We suppose that a developed national QI implies a large number of accredited certification bodies. On the
other hand, the size of certification bodies differs when comparing the large international companies (i.e.
SGS, Bureau Veritas and TÜV) with smaller firms with a national or a thematic focus. Also interesting is the
emergence of international networks of smaller certification bodies1.
However, there is no international statistic on the number of accredited certification bodies in every country.
Only some accreditation bodies list the names of their accredited certification bodies on their Websites.
Therefore we do not use the number of accredited certification bodies as part of our indicator.
In regard to the output of Certification, we are using the ISO statistic on ISO 9001 issued as a proxy variable.
But this has two limitations: firstly, there are many more certification schemes than ISO, such as the Better
Cotton Initiative, Fair Trade or GlobalGAP2; secondly, there are many more standards in ISO than ISO 90013, for
example, Environmental Management Systems (14001), Information technology (27001), and ISO 13485 which
gives quality management system requirements for medical devices, among others. Nevertheless, ISO 9001 is
by far the best seller.
1) i.e. IQNET (http://www.iqnet-cer tification.com)
2) As the number of private/ voluntar y standards increase continuousl y, it is diffi cult to get an overv iew. The Standards Map is of the Internat ional Trade Center
is an online tool that enables analyses and comparisons of private/voluntary standards (see http://w ww.standardsmap.org/).
3) ISO has developed over 18 500 International Standards on a var iety of subjects and so me 1100 new ISO standards are published ever y year (see ht tp://ww w.iso.org).
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Ulrich Harmes-Liedtke, Juan José Oteiza Di Matteo
Metrology
The International Bureau of Weights and Measures (BIPM) acts in matters of world metrology,
particularly concerning the demand for measurement standards of ever increasing accuracy, range and diversity,
and the need to demonstrate equivalence between national measurement standards. In 1999, the directors
of the national metrology institutes of thirty eight Member States of the BIPM and representatives of two
international organizations signed a Mutual Recognition Arrangement (CIPM MRA) for national measurement
standards and for calibration and measurement certificates issued by NMIs. A number of other institutes
have signed since then. This Mutual Recognition Arrangement is a response to a growing need for an open,
transparent and comprehensive scheme to give users reliable quantitative information on the comparability of
national metrology services and to provide the technical basis for wider agreements negotiated for international
trade, commerce and regulatory affairs. The CIPM MRA has now been signed by 48 Member States and covers
a further 122 institutes designated by the signatory bodies.
The International Organization of Legal Metrology (OIML) is an intergovernmental treaty organization
whose membership includes Member States, countries which participate actively in technical activities. It was
established in 1955 in order to promote the global harmonization of legal metrology procedures. Since that
time, the OIML has developed a worldwide technical structure that provides its Members with metrological
guidelines for the elaboration of national and regional requirements concerning the manufacture and use of
measuring instruments for legal metrology applications.
2.1.3 Available information
Categorical and quantitative data can be gathered from websites.
Among the first things we found was basically that a country (or organization) can be classified by: membership
or non membership; categories of membership (full or body member, associate, participant, partner, observer,
etc); signatories or non signatories to some agreement (MRA, MLA); and participation in committees. This set of
data will be used mainly to determine the sample of countries in the next section, and later will be part of the
QI indicator itself. Membership and signatories’ qualities could be considered as an input of the QI system. But
QI performance is not guaranteed by this condition since it wouldn’t be sufficient.
The quantitative information used in this paper relates to that performance and reveals some evidence about
the stage of development achieved by each QI system. This second set of data is considered as the system
output. Quantity of bodies and issued certificates are the most relevant statistics collected due to the fact that
they are mostly freely accessed, and easy to interpret and compare.
The above considerations are summarized in the following table, from which the basic matrix for the
measurement of the QI will be obtained.
QI system Inputs Outputs
Accreditation • Membership of: IAF, ILAC
• Signatories to: MLA, MR A
• Regional agreements
• Total Accredited Bodies ( TAB) by national accreditation bodies
Metrology • Membership of: CIPM, OIML
• Signatories to CIPM MRA
• Calibration and Measurement Capabilities (CMC) issued and recognized
• Key and Supplementary comparisons practiced
Standardization • Membership of: ISO, IEC, ITU
• Participation in ISO committees
• Participation in Technical Committees
• Number of standards by country (local and international)
Certification • Accredited certification bodies
(not used because of missing data)
• Number of ISO 9001 certifications issued
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Measurement of Quality Infrastructure
2.1.4 Sample definition
2.1.4.1 Starting point: WTO members
The importance of quality infrastructure in trade is well accepted both nationally and internationally because
it promotes the free movement of goods and services while reducing technical barriers and nontariff barriers
(ITC, WTO and UNCTAD 2005). In turn, adherence to quality standards by producers of goods and services sold
globally gives the consumer a better assurance of their safety, health and environment related aspects (Guasch
2007).
However, the number of technical regulations and standards adopted by countries has grown significantly in
recent years. This has led to the creation of impediments to free trade due to the lack of harmonization in the
quality standards of the countries engaged in global trade (World Trade Organization 2005).
The WTO, through its Technical Barriers to Trade Agreement (TBT), tries to ensure that regulations, standards,
testing and certification procedures do not create unnecessary obstacles. This commitment includes the
obligation for member states to establish national enquiry points and to keep each other informed about the
new regulations. In addition, the WTO groups together 152 member states and 30 observer countries (which
must start accession negotiations within five years of becoming observers). Of the 192 countries recognized by
the UN, 182 belong to the WTO. Global trade is well represented by those members and observers.
Although not all WTO states will be sampled in this paper, this set will serve as a starting point for the definition
of our target group.
2.1.4.2 Clustering criterion within the sample: development perspective
Every year through their Development Assistance Committee (DAC), the OECD countries approve the List of
Recipients of Official Development Assistance (ODA). These countries are divided into income groups (Other
low income, Lower Middle Income, Upper Middle Income) based on Gross National Income (GNI) per capita
as reported by the World Bank, with the Least Developed Countries (LDCs) as defined by the United Nations.
Coincidentally, there are also 152 countries in the 2009 list but only 83% of them are WTO members (U N C TA D
2007).
LDC in particular are hardly covered by the international quality system: only four members of ISO (Tanzania,
Bangladesh, Ethiopia and Sudan), and one of OIML (Tanzania) are included. This time, these countries will not
be covered by our radar.
So, three categories will be considered, depending on whether the country is a donor (DAC), recipient (ODA),
or neither (non ODA).
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Ulrich Harmes-Liedtke, Juan José Oteiza Di Matteo
2.1.4.3 The best set and the sample selection
As is shown in the table below, ITU and ISO sets represent quite well the proportions of our starting group
(WTO) classified according to the ODA-DAC list, probably because of the large sample size of each. Both are
better than any other set in terms of representativeness. If we look at the following sets (BIPM, OIML, IAF, IEC,
ILAC countries) these are fairly homogeneous in their numbers but with a smaller sample size. Members of BIPM
draw some advantage over these because they represent WTO members better. ONU countries are included
only as a reference.
All WTO countries (members and observers) also belong to the ITU, so the sample choice is between members
of ISO and BIPM.
The larger number of BIPM countries in the international QI system produces a more homogeneous set (98%
of them belong to another international body). Indeed, if we take all ISO members, we find a significantly
lower percentage (73%). Therefore, BIPM members will be chosen as the target group in this paper. So we
intend to give more weight to the quality of information in terms of reliability and availability rather than the
representativeness of the sample, at least on this occasion. Further research is needed to assess the quality of
the information on a broader base of countries.
ODA non ODA DAC Total Sample Size
WTO* 69% 19% 12% 10 0% 182
ITU 69% 19% 12% 10 0% 183
ISO 57% 21% 22% 10 0% 101
BIPM 43% 19% 39% 100% 54
OIML 41% 21% 38% 10 0% 56
IAF 40% 21% 40% 100% 53
IEC 38% 23% 39% 100% 56
ILAC 37% 23% 40% 100% 52
UNO Countries 79% 9% 11% 100 % 192
*WTO M embers and Obse rver s included. For other organizations Full Me mber considered.
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Measurement of Quality Infrastructure
2.1.4.4 The sample
The table below shows the 54 members of the BIPM and their classification according to the aforementioned
criterion. However, Australia and New Zealand will be taken as a single economy because of their degree of
integration with regard to the QI system.
The abbreviations used are: (HI) High Income, (UMI) Upper Middle Income, (LMI) Lower Middle Income, (OLI)
Other Low Income and refer to the World Bank classification.
There are 45 signatories of the CIPM MRA among the sample countries. The vast majority of them are highly
integrated into the international system of QI. Indeed, over 80% are full members of each of the following
organizations: ISO, IAF, ILAC and BIPM. 74% of the world population and 95% of world GDP is represented by
these economies according to data from the World Bank (2008).
DAC ODA Non ODA
Australia (HI) Argentina (UMI) Czech Republic (HI)
Austria (HI) Brazil (UMI) Hungary (HI)
Belgium (HI) Chile (UMI) Israel (HI)
Canada (HI) Croatia (UMI) Korea, Republic of (HI)
Denmark (HI) Kazakhstan (UMI) Singapore (HI)
Finland (HI) Malaysia (UMI) Slovak Republic (HI)
France (HI) Mexico (UMI) Bulgaria (UMI)
Germany (HI) Serbia (UMI) Poland (UMI)
Greece (HI) South Africa (UMI) Romania (UMI)
Ireland (HI) Turkey (UMI) Russian Federation (UMI)
Italy (HI) Uruguay (UMI)
Japan (HI) Venezuela, Bolivarian Rep of (UMI)
Netherlands (HI) Cameroon (LMI)
New Zealand (HI) China (LMI)
Norway (HI) Dominican Republic (LMI)
Portugal (HI) Egypt (LMI)
Spain (HI) India (LMI)
Sweden (HI) Indonesia (LMI)
Switzerland (HI) Iran (LMI)
United Kingdom (HI) Thailand (LMI)
USA (HI) Kenya (OLI)
Korea, DPR of (OLI)
Pakistan (OLI)
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Ulrich Harmes-Liedtke, Juan José Oteiza Di Matteo
2.2 Measurement of QI components
2.2.1 Metrology
As indicated by the BIPM, metrology is the science of accurate and reliable measurements. But not all
countries have a quality infrastructure with the same measurement and calibration capabilities. A key criterion
for evaluating these capabilities is not a precise measurement, but the highest reliability of measurement
capabilities declared. These are called Calibration and Measurement Capabilities4 (CMCs) and are awarded to NMI
through the CIPM MRA (International Committee of Weights and Measures - Mutual Recognition Agreement).
The CMCs are issued in a database managed by the BIPM in Paris and published online5 .
One approach to measuring development and reliability of the national metrology would be provided by the
number of CMCs given to the NMI of the host country6. This statistic would measure three aspects of the
system: firstly, the development achieved from the point of view of its size. We suppose that the greater the
amount of declared capability, the greater the infrastructure needed to support it. Secondly, a greater number
of CMCs would also show the diversification of skills. We assume that the system is at a more advanced stage
of development when its supply of services is more diversified. Thirdly, recognition by other members of the
club is incorporated into this proposed measure because CMC certificates are issued within the field of the
agreement.
Additionally, we would consider the number of CMCs but in relation to population in an attempt to measure
the metrology system relative to the domestic market. Here there is a significant “size effect” produced by the
scale of economies, but there could also be an issue of system efficiency that may explain differences between
countries.
The BIPM also gives information about the set of comparisons conducted by NMIs to test the principal
techniques and methods in the field. These are called Key or Supplementary Comparisons and are carried out
by two or more bodies organized by the Consultative Committees or the Regional Metrology Organizations
(RMO). The first comparisons are open to laboratories with the highest technical competence and experience.
The second set are carried out by RMOs to meet specific needs not covered by key comparisons, including
comparisons to support confidence in calibration and measurement certificates. So, the larger the number of
comparisons, the higher the degree of interaction with other members of the international quality infrastructure
system, and possibly the better the metrological capacities that might be acquired or spread.
4) The highest leve l of calib ration or measurement normally offere d to client s, expressed in te rms of a con fidence l evel of 95 %,
sometimes referred to as best measurement capability. (http://www.bipm.org/utils/en/pdf/mra_glossary.pdf).
5) In some countries, the NMI delegate some wor k to secondary calibration laborator ies, which can be private or public entities.
These use secon dary s tandards traceable in NMI to calib rate the i nstru ments of their consumers.
The concept of tra ceability means an unbroken chain of co mparison measurement s with instruments of increasing accuracy (lower measurement uncerta inty)
star ting with the instrument used in the industry and moving up to national standard (Sanetra 2007).
6) Our consultation of metrology exp ert s confirmed the ut ility of the CMC s indicator. As CMCs require comparison measurement s with similar uncerta inty
there are no better indic ators. N evert heles s, the number itself may re fer to dif ferent levels of met rological competence, i.e. a NMI may get 10 CMCs for mass pieces
on a low level or get 10 CMC s on primary normals, but there is world of difference bet ween the two.
14
Measurement of Quality Infrastructure
2.2.2 Accreditation
Accreditation is defined as the procedure by which a body gives formal recognition that an organization
or person is competent to carry out specific tasks (Guasch 2007). Once the accreditation is issued by the
body, the organization becomes an Accredited Body. Accreditation is sought on a voluntary basis as proof of
competence in a given area. Most countries have a single national accreditation body responsible for all areas
of accreditation. It can be either a public or a private not-for-profit organization. Accreditation covers various
areas such as: management system certification bodies, testing and calibration laboratories, Greenhouse Gas
validation, verification bodies, personnel certification bodies, product and service certification bodies, and
inspection bodies, among the most relevant examples.
Thus, a greater number of accredited bodies could lead to the diffusion of the competency, authority and
credibility of those bodies.
We collected the Total Accredited Bodies (TAB) from each economy, using as a source the websites of all
National Accreditation Bodies included in the sample. TAB will be the output of this QI component. We
may recall that 10 of the 54 members of our group are members of neither IAF nor ILAC, however, their
accreditation bodies provide information about the certificates issued (except for three: Mexico, Kenya and
Korea DPR).
2.2.3 Standardization and Certification
As ISO pointed out, standards ensure desirable characteristics of products and services such as quality,
environmental friendliness, safety, reliability, efficiency and inter changeability and at an economical cost. ISO
launches the development of new standards in response to sectors and stakeholders that express a clearly
established need for them.
The best selling standards are:
• ISO 9001:2008 Quality Management Systems
• ISO 14001:2004 Environmental Management Systems
• ISO/IEC 27001:2005 Information technology - Security techniques
- Information security management systems
• ISO 31000:2009 Risk Management
The most popular certification is ISO 9001 (2000 and 2008 editions), for which almost a million certificates had
been issued in 176 countries and economies up to the end of December 2008.
This makes the number of issued ISO 9001 a relevant indicator to measure the penetration of the
standardization in the economies. The ISO survey 2008 provides this information disaggregated by country.
Again, the size of population is closely associated with the number of ISO issued. Thus, this data will be
presented in relative terms.
15
Ulrich Harmes-Liedtke, Juan José Oteiza Di Matteo
ISO standards are developed by Technical Committees (TC) comprising experts from the industrial, technical
and business sectors which have asked for the standards, and which subsequently put them to use. The experts
participate as national delegations, chosen by the ISO national member institute for the country concerned.
These delegations are required to represent not just the views of the organizations in which their participating
experts work, but of other stakeholders too.
Information about the number of Technical Committees in which each country participates is available on the
ISO website. It will be used as input in this work in order to measure the degree of participation in international
development of quality standards.
2.3 The Indexes
2.3.1 The basic measure
Index (CMC, ISO, TAB)
It measures the output of three of the four sectors of the QI (Metrology, Standardization and Accreditation).
The indicator is constructed from three different sources, all available on the Web: CMCs, ISO9001 and TAB.
These outputs are not the only ones given by the system, but are freely available on the Internet, so they are
easily observable. In all three cases, the value recorded in each variable is the number of certificates issued by
the competent authority. As already mentioned, the CIPM issues the CMC certifications to the NMI; ISO 9001
certifications are given through an accredited member in the domestic economy; and TAB counted for each
country comes from the websites (54 in total) of the national bodies responsible for that accreditation.
Due to the index composition, it gives better positions to the largest countries, from the point of view of their
population and/or their production. Indeed, the three variables comprising it are positive but only moderately
correlated with population and GDP. No wonder then that the top positions will generally be occupied by the
most powerful countries and/or populations in the world, and the lower ones by the smaller and/or poorer
countries. Furthermore, the three indicator variables are positively correlated with each other, so that countries
with high records of one tend to have high registers in the other two. The same applies to intermediate and low
levels. We think then that the effect of the size of economies significantly impacts the behavior of this composite
indicator. It is important to take this into account in order to give a correct interpretation of the indicator and
not overstate its explanatory power.
On the other hand, it has the advantage of being a „pure“ indicator which doesn’t resort to using proxies,
usually used to measure complex phenomena. In this case, the phenomenon is observed directly. But it is clear
that this set of variables is far from exhaustive, and that the view they give us is direct, but partial.
Some relevant questions arise when we deepen our analysis of the information provided by this indicator.
16
Measurement of Quality Infrastructure
To begin with, what does it means for two countries to have equal values for this composite index? Well, as
previously mentioned, it is to be expected that CMCs, ISO and TAB will have similar values, that is, all relatively
high, or all low, or all three variables at intermediate levels. So, can we say that two countries such as the Korean
Rep. (22.42) and Japan (23.18) have a similar QI? We cannot answer this question with the information available,
but we can give some pointers towards clarifying the matter. Firstly, it is noted that Japan has a population of
almost 128 million in contrast to the Rep. of Korea‘s 49 million, that is to say, two and half times larger. Its GDP
is also higher: 4.4 billion as opposed to 1.4 billion (PPP). Here the ratio is approximately 3 to 1. It is clear that
these QIs serve different needs, at least from the standpoint of the scale. However, as we said, the QI seems to
be similar if we look at the number of certificates produced by each system. Some hypotheses to explain the
above could be:
a) There is a difference in the efficiency of the systems. Japan is more efficient than the Korean Republic
despite the fact that it has equal QI, but produces more and has larger domestic markets.
This hypothesis would make sense if we think that two countries can convey various stages of development
of their QI. In turn, the market orientation of their internal or external production systems and opening
of the economy to the flow of imports could determine a productivity differential because the exposure
to international trade competition requires better and more efficient development of quality systems.
b) QI not recognized internationally. We might think that a significant part of the product of a country is
generated outside the international recognition platform considered in this paper. We are not saying that
Japan produces products of low quality but that their quality is not recognized at all. This could relate to an
economy that produces mainly for the domestic market.
c) Differential quality. The previous point leads us to think of a more extreme situation.
If two economies have the same QI (as measured) but one produces more than the other and is more
populated, then, in the latter the quality of the infrastructure is not very widespread.The result would be
a negative differential in quality. This could be true only if comparing equally efficient systems.
Perhaps the issue is even more complex, and in reality several of the factors mentioned above are operating
simultaneously. Further research would be needed to shed light on this issue.
The above analysis suggests the need to relativize this way of measuring the QI if we are to do justice to the
countries involved in the sample.
2.3.2 Measuring in relative terms
Index (CMC/POP, ISO/POP, TAB/POP)
Constructed in this way, the first indicator measures the number of CMC, ISO, and TAB for each million
inhabitants. That is, each variable in terms of population. Countries with large populations and low QI will be
punished with lower ranking positions. A large population must be accompanied by a well-developed QI if an
economy wants to be highlighted in the field of quality infrastructure with international recognition. Countries
that favor the internal versus external market are not expected to achieve the best scores in the rankings
because they will need an internationally less well recognized QI to meet its demands. Small countries with
large export profiles will be the best candidates for upper positions. Thus, the population size serves to relativize
the QI and partially mitigate the problems of scale, efficiency, and quality of systems, but on the other hand,
incorporates a bias which must be addressed later.
Index (CMC/GDP, ISO/GDP, TAB/GDP)
Another alternative to relativize the QI would use GDP. We are aware of the critique on the use of GDP as the
weight or indicator, since it can be positively correlated with factors that diminish quality of life, and at the same
17
Ulrich Harmes-Liedtke, Juan José Oteiza Di Matteo
time may not reflect factors that are well developed in the economy and contribute to social welfare7. Despite
this criticism, we use the GDP in this section since it is easy to observe and is an indicator universally taken for
comparison in economic research.
The results in the ranking do not change substantially if we do both lists, with a few exceptions. Now the
number of CMCs, ISO and TAB is divided by the value of GDP (billion of GDP: PPP World Bank 2008). Note that
the comments made earlier also apply when we use GDP to relativize the QI. That is, the larger producers in
the world require a high amount (comparatively speaking) of CMC, ISO and TAB to be located at the top of the
ranking. The relative exposure of the economy to international trade could make the difference again between
the two. The efficiency of the system could also partly explain the differentials.
We said recently that changes in rankings are not substantial if relativized to population or GDP, except for some
countries. Let’s consider these specific cases.
For the total sample, changes are on average of six positions, sometimes gained and sometimes lost. Only ten coun-
tries diverge from the average in more than one standard deviation above. That is, only the countries in the table
above change more than ten places when moving from one list to another. The biggest change is for Norway, which
drops 20 positions. So, when using population its place in the list is 16th, but in relation to GDP, it falls to position 36.8
Of the ten in the table, most gain positions when the QI is split between the GDP. Only countries with high
GDP per capita such as the USA, Ireland and Norway lose ground so drastically. Indeed, these three countries
are amongst the four highest GDP per capita in the world (all three are DAC). Moreover, those gaining posi-
tions are the countries that are mid-table and below on GDP per capita. This could skew the final results at the
extremes of the list, just like when we use population. The problem should be solved somehow.
Finally, among the variables, population and GDP there is a very strong positive correlation (Spearman correla-
tion = 0.83), so that the use of one or the other to relativize the QI does not generate large differences in the
end. What should we use then? Population or GDP? The GDP of an economy is more volatile than the size of its
population over time, so our indicator would be more sensitive to possible changes in the QI if we relativize by
number of residents. This rationale finds support in the fact that the two variables are weakly associated (corre-
lation 0.34), unlike GDP which maintains a direct and very close relationship with the level of Index (CMC, ISO,
TAB) (correlation 0.80). In addition, GDP is not always comparable between OECD countries and least devel-
oped countries. For these reasons, we will use population to construct our leading indicator. However, in the
Appendix we can see how countries are rated using both methods.
QI relative to population
ranking position
QI relative to GDP (PPA)
ranking position
Rank difference
Romania 27 10 17
Chile 30 14 16
China 41 25 16
Serbia 21 714
Malaysia 33 21 12
Bulgaria 12 111
Croatia 26 15 11
USA 37 49 -12
Ireland 10 23 -13
Norway 16 36 -20
7) For example: GDP treats crime, divorce, and natural disasters as economic gain; GDP ignores the non-market economy of household and community; GDP t reats t he depletion of
natural capital a s income; G DP increases with polluting act ivities and aga in with cl ean ups; GD P ignore s income distribution and the drawback s of life in foreign assets.
8) A specific feature o f Norway is the 80 % of its GDP is due to oil produc tion. T his may explain why it falls in the ranking positions. Fur ther research o n sectoral ef fects is neces sary.
18
Measurement of Quality Infrastructure
2.3.3 The relational dimension
Index (Key and Supplementary Comparisons, TC Participation, Membership)
The data matrix presented earlier in this chapter shows different inputs and outputs of the quality system of a
country that could be used for measurement of QI. All of them are observable via the Internet. From this matrix,
three additional variables to those already considered were taken into account to enrich our indicator. These are:
I. Key and Supplementary Comparisons carried out by the NMI in coordination with peer bodies in other
countries. These field experiences are conducted under the auspices of the CIPM.
II. Participation in Technical Committees of the International Standardization Organization. Those are given
within the ISO and follow the interest in the development of standards in specific areas. The rule is that
these groups include representatives from various countries.
III. Full membership of international organizations committed to the development of QI at international level
(WTO, IAF, ILAC, CIPM, OIML, ISO, IEC, ITU).
There is a common element in all three factors: the linkage or relationship between the participants. The sys-
temic dimension appears again here. This allows us to group the new variables to form a second indicator of the
quality infrastructure under the name of Participation in the international system of QI.
We assume that the greater the participation in these three areas, the greater the degree of development of
the QI. The dissemination of good practices, learning spaces and knowledge sharing, and the benefits of being
recognized by other club members, are elements that would support our assumption.
The new indicator will be summarized as Index (K&S Comp., TC Part., Member.). In general, one should not
necessarily expect countries with high values for this index to also record high values for Index (CMC/POP, ISO/
POP, TAB/POP), and vice versa. The evidence shows that the association between them is weak. This allows us to
think that we are seeing a different dimension of the QI, which is quite evident if we look at the kind of infor-
mation that is grouped into this new indicator. Therefore, we would be adding new information, which is not
redundant, thereby increasing the explanatory power of the measuring instrument. To preserve this advantage
it will not be appropriate to relativize the three components of the new indicator using population. If we did
this, the correlation between them would reach 90%, which would greatly weaken the informational power of
the new component. Moreover, when considering the absolute amounts of K&S Comp., TC Part. and Member-
ship, we have a chance to partially resolve the problem of bias that we mentioned earlier.
2.3.4 The composite indicator
Index (QI/POP)
If we give equal value to the number of licenses per capita and participation in the international system of QI,
we can construct a composite indicator, where the weight assigned to each component is the same. That is,
we would be averaging both indices. We have no reason to assign different weights, so the equity criterion has
been chosen.
19
Ulrich Harmes-Liedtke, Juan José Oteiza Di Matteo
The composite index is called Index (QI/POP). Below we can see the mathematics behind the indicator.
References:
1. QI = Quality Infrastructure
2. POP = Country Population
3. CMC = Total Calibration and Measurement Capabilities
4. ISO = Total ISO9001 issued
5. TAB = Total Accredited Bodies
6. K&SComp. = Total Key and Supplementary Comparisons
7. Tech.Comm. = Total Technical Committees participations
8. Membership = Number of Memberships of international QI system
The diagram below is an adaptation of a graphic used frequently in PTB documentations on Quality Infrastruc-
ture and Value Chains (Sanetra 2007). It shows in the red area the location of the measures of our main indica-
tor. Note that connections on the left side of the diagram were given little consideration because of the avail-
ability of information and our pragmatic approach, but future research should clarify this crucial issue.
National Quality System
INTERNATIONAL SYSTEM
NATIONAL VALUE CHAIN
Applies to all
products and
processes
Metrology
Testing
laboratories
Standardization
Certification
Accreditation
Equipment calibration
Reference materials
Assays, Research
Analysis
traceability
Index(QI/Pop) =
• Index
(
CMC ISO TAB
Pop Pop Pop
, ,
)
=
(
CMCi/Pop ISOi/Pop TABi/Pop
max.value max.value max.value
+ +
)
x100
3
• Index(K&SComp.,Tech.Comm.,Membership)=
(
K&SCompi
max.value +
TechCommi Membershipi
max.value max.value
+
)
x100
3
Index
(
CMC ISO TAB
Pop Pop Pop
, ,
)
+Index(K&SComp.,Tech.Comm.,Membership)
2
20
Measurement of Quality Infrastructure
The connection between the main indicator and the International System of QI is stronger. This is an advantage since
the quality of data is higher and comparisons tend to be reliable. On the other hand, the measurement of the QI
links with the national value chain represents a much greater challenge than the one proposed in this paper. Their
study could reveal the specifics of each system and would assess their effectiveness in meeting the real needs in NQS.
Coming back to the issue of bias, we can say that this composite indicator has the advantage of having eliminated
the association with population size (correlation is close to zero). That is, countries with extreme values for popula-
tion do not necessarily need to be located at the ends of the ranking. The reason for this is that we haven’t relativized
the participation in the international system of QI, which somehow compensates countries "punished" for having
large populations, and in turn, does justice to those small countries that enjoyed good ranking positions, provided
of course they actively participate in the scheme. Indeed, there doesn’t seem to be a specific pattern among Index
(QI/POP) and population. The scatter plot below illustrates this argument. Importantly, we have removed China and
India for being extraordinarily populous so we can better see the lack of association between variables.
In summary, the advantages and disadvantages of the indicator can be stated as follows:
a) It is simple in design, which facilitates comprehension and analysis, especially if we consider that one
purpose of the paper is to propose a methodology to encourage discussion of the issue and make room for
as much improvement as possible. It is also replicated, thus ensuring the transparency of the method.
b) It is well behaved, in the sense that the distribution is relatively symmetric and homogeneous. This allows the
mobility of the countries in the ranking, as long as enough of them change one or more variables. So, there
are no “unattainable” positions in the ranking. The box plot illustrates this advantage. The 50th percentile of
the distribution (the median) is quite centered, and there are no atypical or extreme outliers. Therefore, there
is symmetry and homogeneity. These two qualities were observed in widespread indexes such as the Corrup-
tion Perception Index (Transparency International), Global Competitiveness Index (WEF) and Innovation
Capacity Index also.
10 20 30 40 50 60
50
100
150
200
250
300
350
Population (millions)
Quality infrastructure/Population
United States
Germany
Indonesia
Pakistan
Chile
Iran
Argentinia
Greece
Australia
Argentinia
Sweden
United Kingdom
Turkey
Dominican Republic
21
Ulrich Harmes-Liedtke, Juan José Oteiza Di Matteo
Box Plot for QI / POP scores
c. It reflects two different and complementary dimensions of the QI system. One has to do with what
happens locally, and another with what happens internationally. Indeed, the certifications ISO, TAB, CMC,
are awarded to organizations that act locally (enterprises and public institutions typically), while K&S
Comparison, Technical Committees Participation and Membership correspond to the international arena.
And as we saw earlier, neither indicator is redundant.
d. However, it is unclear whether the diffusion of QI reaches its final destination: the companies and individual
users. For example, suppose that we know that a certain country has international recognition for its QI,
which actively participates in the exchange of experiences and knowledge at international level, that the
local members are accredited to practice their skills, and there are "guards" evaluating the technical compli-
ance of those members, but in the end, we can’t assess whether the ultimate purpose of QI is achieved. This
is perhaps the main disadvantage of this methodology.
2.4 The Quality Infrastructure rankings
This section shows the global ranking according to the QI/POP measurement. In addition to the proposed mea-
suring methodology, other composite indicators are incorporated for comparison purposes. This will help us to
see the coherence and consistency of the proposed index. In the first column countries are ordered by our main
indicator of QI in relation to Population–Index (QI/POP). The second and third columns shows the rankings ac-
cording to the sub-indicators that make up the composite index.
The last column presents the ranking for Index (QI/GDP) which was calculated in the same way as our main
composite indicator, but this time GDP was used to relativize.
20
40
60
0
Quality infrastructure / Population
22
Measurement of Quality Infrastructure
Included in the Appendix for detailed analysis are the multiple rankings for DAC, ODA and non ODA countries
showing how they are sorted according to all variables considered in the composite indicator.
Rank Index (QI/POP) Score Sub-Index (CMC/
Pop,ISO/Pop,TAB/
Pop)
Sub-Index
(K&SC,TC,Mem)
Index (QI/GDP) Score
1Sweden 64.3 Sweden Germany Czech Republic 60.9
2Switzerland 62.9 Switzerland United Kingdom Slovakia 59.6
3Germany 61.0 Slovakia France Germany 58.6
4Czech Republic 58.9 Czech Republic USA Sweden 58.4
5Italy 58.2 Finland Japan Hungary 57. 7
6United Kingdom 57.1 Hungary Korea, Rep. Bulgaria 57. 5
7Netherlands 56.1 Netherlands China Italy 57.4
8Finland 56.0 Singapore Australia and NZ United Kingdom 54.5
9Slovakia 55.4 Italy Italy Switzerland 53.2
10 France 52.9 Ireland Netherlands Romania 51.9
11 Spain 51.7 Spain Czech Republic France 51.3
12 Republic of Korea 50.3 Bulgaria Romania Spain 50.6
13 Hungary 49.1 Uruguay Spain Republic of Korea 49.7
14 Japan 48.1 Austria Poland China 49.3
15 Australia and NZ 47. 0 Denmark Russian Fed. Netherlands 48.6
16 Austria 46.3 Norway Switzerland Finland 47.6
17 USA 45.4 United Kingdom India Japan 47. 2
18 Romania 43.6 Portugal Finland Australia and NZ 44.9
19 China 42.2 Germany Sweden USA 44.2
20 Poland 41.0 Greece Austria Poland 43.7
21 Denmark 40.0 Serbia Slovakia Serbia 43.3
22 Singapore 39.6 Republic of Korea Canada Portugal 41.3
23 Ireland 39. 5 France South Africa Austria 41.2
24 Belgium 38.6 Israel Brazil Russian Federation 39.9
25 Russian Federation 38.6 Belgium Belgium India 38.4
26 Portugal 38.2 Croatia Hungary South Africa 37. 7
27 Norway 38.0 Romania Turkey Belgium 37. 6
28 Canada 38.0 Australia and NZ Portugal Denmark 35.8
29 Bulgaria 37. 5 Canada Denmark Canada 35.7
30 India 34.9 Chile Mexico Brazil 34.6
31 South Africa 33.7 Poland Norway Uruguay 34.2
23
Ulrich Harmes-Liedtke, Juan José Oteiza Di Matteo
Rank Index (QI/POP) Score Sub-Index (CMC/
Pop,ISO/Pop,TAB/
Pop)
Sub-Index
(K&SC,TC,Mem)
Index (QI/GDP) Score
32 Brazil 32.3 Japan Argentina Turkey 34.0
33 Greece 31.9 Malaysia Egypt Ireland 32.3
34 Turkey 31.3 Argentina Ireland Greece 32.1
35 Serbia 30.0 Russian Federation. Indonesia Norway 31.3
36 Argentina 28.1 Turkey Thailand Malaysia 31.1
37 Israel 28.0 USA Greece Argentina 31.0
38 Mexico 2 7.4 South Africa Bulgaria Singapore 30.6
39 Malaysia 26.4 Kazakhstan Malaysia Croatia 2 9. 5
40 Croatia 25.3 Thailand Serbia Israel 29.2
41 Uruguay 24.7 China Singapore Thailand 28.9
42 Thailand 24.6 Brazil Pakistan Mexico 28.1
43 Egypt 23.7 Mexico Israel Chile 2 7.4
44 Indonesia 23.7 Korea, DPR Iran Indonesia 26.4
45 Iran 20.4 Iran Croatia Egypt 25.1
46 Pakistan 20.3 Dominican Republic. Kenya Iran 22.1
47 Chile 19.7 Indonesia Chile Pakistan 21.7
48 Kenya 15.0 India Korea, DPR Kazakhstan 16.2
49 Kazakhstan 12.3 Egypt Kazakhstan Kenya 16 .1
50 Korea, DPR 11. 8 Venezuela Uruguay Cameroon 9.1
51 Cameroon 9.1 Pakistan Cameroon Venezuela 9.0
52 Venezuela 8.7 Kenya Venezuela. Dominican Republic 8.2
53 Dominican Republic 6.7 Cameroon Domin Rep. Korea, DPR n.d.
Our main indicator (QI/POP) shows that the top half of the table is dominated by 17 of the 20 DAC countries,
interspersed with 8 of the 10 non ODA. All ODA countries except China are located in the lower half of the list.
Topping the list is Sweden, which stands out mainly in the area of accreditation. It has three times more bodies
accredited relative to population than its immediate follower (Slovakia). This makes a significant contribution to
its final score, which holds the best position in the ranking9.
Among the DAC list, Greece shows by far the worst performance in terms of QI development. In particular, its
low level of participation in the international system concerning QI has relegated this economy.
9) Sweden has accredited 1200 inspectio n bodies and is the world lea der, but the se mainly refere to t ire-pressure testing at gas st ations.
24
Measurement of Quality Infrastructure
On the other hand, China stands out because, despite being considered an emerging economy that receives
financial assistance from the international cooperation, it is the best ranked among the sample for the basic
measure Index (CMC, ISO, TAB). The size of this economy could easily explain the position. China‘s transition
can also be seen in the development of quality infrastructure. Participation in the QI international system is
also outstanding, ranking seventh on the list. For the main indicator, China is the best ranked among the ODA
countries.
As usual, BRIC countries present similar behavior. Indeed, if we look at the QI/Pop index, the best positioned
is China (19), then Russia Fed (25), followed by India (30) and finally Brazil (32). Finally, the proximity is even
greater if we remove the DAC countries between the best and worst ranked. Only eight positions then separate
the first from the last BRIC.
The bottom of the main rankings is dominated mostly by the same countries: Pakistan, DPR Korea, Kenya,
Kazakhstan, Cameroon, Dominican Republic, and the Bolivarian Republic of Venezuela. These are the countries
with one or more indicators in absolute zero, either because the information is not available or because they
record that value for the variable. These cases can be seen in the annexed database.
Below, countries are grouped into four different ranks according to the score obtained on the indicator. The
grouping is done by an algorithm that looks for a natural separation of the cases (SPSS software). On the world
map the countries are shown in different colors.
Ranges for quality infrastructure / population means
48,1 to 64,3 (14)
34,8 to 48,1 (16)
23,6 to 34,8 (14)
6,6 to 23,6 (9)
no data avaiable
25
Ulrich Harmes-Liedtke, Juan José Oteiza Di Matteo
2.5 Limitations and potential improvements
There are risks when measuring a complex phenomenon such as the QI with a general and simple indicator like
the one presented here. For example, it could happen that an economy develops its QI but this has not im-
mediately been reflected in the index. Furthermore, the amount does not guarantee quality. A large number of
non-respected rules have no positive effect on the quality of services provided. In turn, certifications could be
obtained without following all protocols and guarantees. Finally, an equal number of accredited members may
offer very different skills.
In short, there has been a trade-off between the initial objective of the QI measurement (a pragmatic approach
that is easy to replicate) and what has actually been achieved methodologically. However, if a comparison of
the QI (as measured) is carried out within more homogeneous groups, then the proposed ranking will make
more sense. This would be the case if we considered the developed countries on the one hand, and the less
developed economies on the other. In fact, we will see later that the performance of the QI in relation to GDP,
exports, competitiveness and transparency, groups countries mostly in the same way.
It is evident that much greater effort is required to investigate this issue, but we also must recognize that this
index can be an exciting starting point which serves to stimulate debate and trigger new ideas.
Some of the potential improvements that could be incorporated into the methodology for measuring the QI
have emerged from the valuable contributions and criticisms received during production of the document.
Specifically, the number of ISO 9000 may reflect very different realities in the case of one obtained in Germany
rather than Guatemala or the Philippines. A certificate for using mechanical scales is not the same as one for us-
ing a high-precision measuring device. The same applies to the number of CMCs and accredited bodies (TAB).
Regarding the former, a user can have easy access to foreign metrology services without any such offer locally.
On the other hand, it could be the case that there is a relatively developed metrological infrastructure but it
does not reach its full potential in relation to the final consumer. The number of accredited members is also sub-
ject to these problems and we cannot compare a laboratory doing basic tests with one that carries out sophisti-
cated research. Finally, due to the normal flow of imports and exports of services, the amount of members may
not fully reflect local realities.
One possibility to improve the indicator would be by making several distinctions that allow us to see more
clearly what we are trying to measure here. For example: a) distinguish the local system's overall system of QI,
since the productive specialization and scale of the countries differ greatly and this affects the type and quantity
of services to be provided by the QI; b) expand the calculation of our main indicator in productive sectors, so
that we can better capture the specificities of each economy (sectors and levels of difficulty linking the certifica-
tion), c) distinguish QI from the scope of mandatory or volunteer practices; d) take into account which countries
have benefited from the resources of international cooperation for the development of QI; and e) incorporate
the net foreign balance of services related to the QI.
Another means of improvement is related to the database. It may be a task for international QI associations to
agree standards and make more and better data available to the interested public. A best practice in this regard
is the availability of development indicators provided by The World Bank (see http://data.worldbank.org/).
26
Measurement of Quality Infrastructure
In this chapter we analyze how the level of QI development is related to relevant economic performance indicators.
Competitiveness, GDP per capita, total Merchandise Exports and Transparency Index, were selected for com-
parison with QI measurement statistics. Below is a brief summary of the methodologies behind each indicator
and also the evidence found about QI performance.
3.1 An over view
Correlation analysis is the appropriate methodology in these cases. The Spearman non-parametric coefficient
will be used in this document. Somehow it is more powerful than the Pearson coefficient for detecting associa-
tions between variables since it is not limited to a linear relationship (Canavos 1993). Indeed, it works with the
rankings of individuals according to two variables (i.e. the higher the position achieved by one variable, the bet-
ter the ranking observed for the other).
The scale used to assess the degree of correlation is as follows: below 0.50 is weak; from 0.50 to 0.65 is mod-
erate; from 0.65 to 0.80 is moderate-to-strong; from 0.80 to 0.95 is strong; and between 0.95 and 1 is very
strong.
Our findings are summarized in the table below.
Spearman
correlation
Quality
infrastructure/
Population
Quality
infrastructure/
GDP
GDP per capita
(PPAWB2008)
Exports
(merchandise
in current USD
WB2009)
Global
Competitiveness
(2009-2010)
Trans-
parency
(2008)
Quality
infrastructure/
Population
1,000 ,918(**) ,705(**) ,637(**) ,689(**) ,707(**)
Quality
infrastructure/
GDP
,918(**) 1,000 ,477(**) ,462(**) ,476(**) ,511( * *)
**Correlation is significant at 0,01 level (bilateral)
Several observations can be made from the table above:
i. All coefficients are significant at the 0.01 level. So, in every case conclusions are highly reliable.
ii. All correlations are positive, supporting the expected relationship between QI development and economic
performance variables. More competitive and transparent countries, with higher GDP per capita and better
export performance, tend to have well-developed quality infrastructure in relative terms. This gives some
coherence to the main QI indicator but also underlines the relevance of a developed QI. However, it would
be incorrect to infer causality from QI to performance indicators, at least from this piece of evidence. A
quality analysis would be required to reach that goal.
iii. Looking at the last four columns of the correlation matrix, the QI/POP index shows stronger associations
with the performance variables compared to the QI/GDP index. But if we look at the table by rows for both
indicators, the coefficients are similar. This evidence could suggest that QI has similar behavior in relation to
performance variables.
3 PERFORMANCE OF QI
27
Ulrich Harmes-Liedtke, Juan José Oteiza Di Matteo
3.1.1 Competitiveness
One simple reason for considering the performance of a country in terms of its competitiveness in relation to
the QI is the undisputed connection between the two. In Guasch (2007), an exhaustive list is given of links with
export growth, productivity, industrial upgrading, and diffusion of innovation, among others.
The main recommendation for developing countries is summarized as follows: “As increased competition among
developing countries in labor-intensive manufactures erodes economic returns, higher-quality markets and high-value
goods are increasingly important to maintaining dynamic competitive advantage. Globally integrated production
networks, typically governed by buyers from developed nations, have raised competitiveness to the top of developing
countries’ policy agendas. Countries need to offer the high-quality products demanded by consumers and global sup-
ply chains and deliver them to markets to meet just-in-time production schedules”.
The Global Competitiveness Index 2009-2010 (Schwab 2009) ranks 133 countries/economies. Developed based
on twelve pillars and a total of 110 variables, this composite indicator is perhaps the most recognized in its field.
Pillars cover the following topics: Institutions; Infrastructure; Macroeconomic stability; Health and primary
education; Higher education and training; Goods market efficiency; Labor market efficiency; Financial market
sophistication; Technological readiness; Market size; Business sophistication; and Innovation.
A detailed analysis of incorporated variables in GCI shows that none of the variables we use in our leading indi-
cator (QI/Pop) are part of GCI. This should be an advantage when interpreting the correlation coefficient as the
relationships detected would be more pure.
An overview of the performance achieved by the 53 economies considered in terms of their QI and competitive-
ness can be seen below.
Figure for Quality Infrastructure and Competitiveness
10 20 30 40 50 60
3,5
4,5
4,0
5,0
5,5
Global Competitiveness Index 2009-2010
Quality Infrastructure/Population
Venezuela
Cameroon
Domin. Rep.
Kazakhstan
Switzerland
Sweden
Germany
Finland
France
United Kingdom
Czech Republik
Japan
Italy
Spain
Singapore
Israel
Greece
Russian Fed.
Thailand
Pakistan
Poland
Austria
Norway
Canada
Ireland Australia
Romania
Kenya
Malaysia
South Africa
Chile
United States
28
Measurement of Quality Infrastructure
The most competitive tend to be the best developed in terms of QI, and the lower the QI, the worse the per-
formance observed. The relationship between QI and Competitiveness tends to be monotonous. Correlation is
moderate-to-strong and positive (coefficient is almost 0.7).
There are countries with large differences in the competitiveness index, which have a similar level of QI/POP,
and vice versa (such as Romania - USA, Chile - Czech Republic, Canada - Sweden). This alerts us to some degree
of uncertainty in the relationship between competitiveness and the development of the IQ (as measured).
3.1.2 GDP per capita
In this case, the information source is the World Bank database. Per GDP per capita is one of the most common
indicators used in economic research since it represents standard of living.
QI development and GDP per capita are in the moderately-to-strongly correlated range. The Spearman coef-
ficient is 0.705 for our main indicator. The tendency of countries to show similar ranking positions for QI and
their performance remains. The following chart illustrates the situation.
Figure for Quality Infrastructure and GDP per capita
Large dispersions can be observed vertically and horizontally. For example, note the position of China and the
Dominican Republic. Both countries have similar per capita income but a very different QI / POP level. It is obvi-
ous that these are two cases where one population is vastly greater than the other. On the other hand, if we
look at China and Norway, which also differ tremendously in population, both have similar QI/POP but with a
large gap in GDP per capita.
In general, high income countries are better developed in terms of QI, and upper-middle to lower income ones
are distributed over the lower graph, mostly on the left-hand side.
10 20 30 40 50 60
10K
30K
20K
40K
50K
GDP per capita (PPA WB2008)
Quality Infrastructure/Population
Norway
Singapore
United States
Switzerland
Sweden
Austria
Denmark
Cameroon
Germany
Czech Rep.
Slovak Rep.
Indonesia
Korea, Rep.
Portugal
Greece
Turkey
Israel
China
Chile
India
Netherlands
Russian Fed.
Venezuela
Kazakhstan
Domin. Rep.
Ireland
29
Ulrich Harmes-Liedtke, Juan José Oteiza Di Matteo
3.1.3 Exports
Breaking down technical barriers to trade is among the first targets of the national quality system. That's why
we discuss export performance and its association with the development of QI through the proposed indicator.
Logic would dictate that the more developed the QI, the better the performance in foreign trade. The develop-
ment of QI seems to contribute in this direction, but with distinct results. In fact, the literature suggests that
this relationship does not follow that simple pattern. Other elements, such as the integration of economies, and
natural or acquired advantages that give it a privileged position as a global supplier of certain products, can
dramatically influence the export performance of a country.
The Spearman correlation is the lowest of those observed. It reaches the value of 0.637, so QI/Pop and Exports
are related in a monotone way but to a moderate degree. The following dispersion chart illustrates this point.
Figure for Quality Infrastructure and Exports
Looking vertically at the two quadrants on the right, we can see huge differences in export performance when
considering similar quality infrastructure. Just look at the three largest exporters in the world (China, Germany,
USA) in comparison to any country that is found in the chart below (Romania, Slovak Republic or Switzerland).
An effect produced by the size of the economies could partially explain these gaps. However, if exports are
made in relation to the population, the results do not improve either.
Once again, we are made to think of the efficiency of the system in meeting the needs of the productive sec-
tor, especially those with export profiles. A QI which is not able to address the needs of enterprises and involve
them in quality management is not sufficient. Small and medium size (SME) enterprises are a special target
group of the Technical Cooperation of PTB, because they are the main form of business in most countries and
crucial for development. However, it is not our intention to include them here for measuring this important is-
sue. Qualitative research should shed light on this topic.
10 20 30 40 50 60
200
600
400
800
1000
Exports (merchandise in current USD WB2009)
QI/Population
China
Japan
United States
Switzerland
Czech Rep.
Domin. Rep.
Cameroon
Germany
Singapore
France
Spain
Italy
Turkey
Mexico
Austria
Greece
Poland
Kenya
30
Measurement of Quality Infrastructure
To provide a better representation of the important link between QI and trade, we tried a different correlation. So on
this occasion we will leave our main indicator – Index (QI/POP) - because it doesn’t reveal the above link as well. In-
dex (QI) does not consider population in the formula, so it relates better to the total exports since both are expressed
in absolute terms. In fact, the Spearman correlation rises up to 0.81 (significant at 1%). Let’s consider a graph.
Figure for Quality Infrastructure and Exports
As we can see, the behavior of countries is now more predictable and streamlined, and the degree of devel-
opment of the QI better discriminates export performance. While we cannot quantify the impact of QI on
merchandise exports, as no causal relationship has been demonstrated between the two, at least the evidence
suggests the need to consider both terms together. In this case, the relationship between the export value and
the size of the quality infrastructure becomes clearer.
3.1.4 Transparency
The Corruption Perceptions Index (CPI) produced by Transparency International could play an important role in
the evaluation of the QI. The CPI measures the perceived level of public-sector corruption in 180 countries and
territories around the world. It is a "survey of surveys", based on 13 different expert and business surveys.
Regarding the relationship between the development of QI and the level of transparency, a reasonable expectation
would be to find a positive correlation between them. In fact, the evidence is in that direction (correlation coefficient
is positive and moderate to strong 0.707). One explanation for this finding would be: less corruption may be associ-
ated with a high degree of political stability, independent and effective judicial systems, adequate resources for audit, a
climate of peace, and strong public institutions able to defend the legal framework and to exercise supervision. Bribery,
influence peddling and unclear rules devaluate critical assets such as trust and credibility. In no way could these prac-
tices contribute positively to the development of QI, as this is based essentially on the credibility of the system's mem-
bers.
10 20 30 40 50 60 70 80
200
600
400
800
1000
Exports (merchandise in current USD WB2009)
Quality infrastructure
Germany
Mexico
Canada
United States
Netherlands
Singapore
Cameroon
United Kingdom
Domin. Rep.
Russian Fed.
Switzerland
China
Japan
France
Greece
Israel
India
Spain
31
Ulrich Harmes-Liedtke, Juan José Oteiza Di Matteo
The following graph shows how the countries are located in relation to their QI / POP and the CPI. Again, the
countries of the first and third quadrant are the same as in previous charts. If we look at the case of Canada and
the Russian Federation, both have a similar level of QI but the degree of transparency is very different. Such
cases may justify using the CPI as the weight of the QI for the purpose of improving the measurement capability
of our indicator.
Figure for Quality Infrastructure and Transparency
10 20 30 40 50 60 70 80
4
2
6
8
Transparency index (2008)
Quality infrastructure / Population
Sweden
Canada
Ireland
Austria
Israel
Chile
Finland
France
Italy
Iran
India
Switzerland
South Africa
Russian Fed.
Korea, DPR
Venezuela
Domin. Rep.
Czech Rep.
Korea, Rep.
Romania
Portugal
Germany
Australia
32
Measurement of Quality Infrastructure
Our initial hypothesis tells us that a country with a well-developed QI is also economically successful; and
inversely, that countries lagging behind in QI are economically less advantaged. The evidence encountered en-
ables us to keep our assumptions intact.
The best performances in terms of competitiveness, exports, GDP per capita and transparency were achieved
in general by the same countries, which boasted the best positions in the rankings for QI development. In turn,
the less advantaged countries corresponded to the least developed in terms of quality infrastructure.
Until now there was no methodology to measure QI which allowed comparison between countries. This is a
virtue of this investigation and at the same time a necessary risk we have to assume if we want to promote the
debate on this particular subject area. Moreover, since there are no other rankings with which to compare our
work, it becomes necessary to deepen and disseminate this analysis in order to improve the effectiveness of
the proposed indicator. But it should be noted that the composite indicator is well behaved in comparison with
other indexes known as GCI.
Concerning the indicator itself, it proved to be a transparent and consistent methodology for measuring the
development of quality infrastructure, but it is only a first approach to the difficult task of measuring the devel-
opment of a system. Further research is needed to identify non-observed variables and ensure their inclusion
in the index of QI development. It would also be desirable to increase the size of the sample, in particular by
incorporating more ODA countries. A qualitative case study would be a fitting complement for this purpose. A
specific survey for the purpose of obtaining that information could also shed light on aspects beyond the sensi-
tivity of our indicator.
Finally, the indicator may serve as a starting point for a comparative assessment of the current state of develop-
ment of QI in the world, enabling the design of policies to standardize quality of products and services. In par-
ticular, a methodology such as this would make it possible to identify the neediest countries in this field, both
for technical and financial assistance.
Country WTO
member
ITU
member
states
IEC full
member
ISO
member
body
OIML
member
states
CIPM
member
states
IAF
member
ILAC
member
Total
Australia xxxxxxxx8
Austria xxxxxxxx8
Belgium xxxxxxxx8
Brazil xxxxxxxx8
Canada xxxxxxxx8
China xxxxxxxx8
Czech Republic xxxxxxxx8
Denmark xxxxxxxx8
Egypt xxxxxxxx8
Finland xxxxxxxx8
France xxxxxxxx8
Germany xxxxxxxx8
Greece xxxxxxxx8
India xxxxxxxx8
Indonesia xxxxxxxx8
Ireland xxxxxxxx8
4 FINAL CONCLUSIONS
33
Ulrich Harmes-Liedtke, Juan José Oteiza Di Matteo
Country WTO
member
ITU
member
states
IEC full
member
ISO
member
body
OIML
member
states
CIPM
member
states
IAF
member
ILAC
member
Total
Italy xxxxxxxx8
Japan xxxxxxxx8
Korea, Republic xxxxxxxx8
Netherlands xxxxxxxx8
New Zealand xxxxxxxx8
Norway xxxxxxxx8
Pakistan xxxxxxxx8
Poland xxxxxxxx8
Portugal xxxxxxxx8
Romania xxxxxxxx8
Slovak Republic xxxxxxxx8
South Africa xxxxxxxx8
Spain xxxxxxxx8
Sweden xxxxxxxx8
Switzerland xxxxxxxx8
Turkey xxxxxxxx8
United Kingdom xxxxxxxx8
United States xxxxxxxx8
Argentina x x x x x x x 7
Israel x x x x x x x 7
Malaysia x x x x x x x 7
Mexico x x x x x x x 7
Singapore x x x x x x x 7
Thailand x x x x x x x 7
Bulgaria xxxxxx 6
Croatia xxxxxx 6
Hungary xxxxxx 6
Iran xxxxx 6
Russian Fed. x x x x x x x 6
Chile x x x x x 5
Kenya x x x x x 5
Serbia xxxxxx 5
Cameroon x x x 4
Kazakhstan x x x x 4
Korea, DPR x x x x x 4
Uruguay x x x x 4
Venezuela x x x x 4
Dominican Rep. x x x 3
34
Measurement of Quality Infrastructure
DAC ODA non ODA
Rank CMCs ISO9001 TAB CMCs/Pop ISO9001/
Pop
TAB/ Pop K&S Com-
parison
TC Participa-
tion
Population (thousands) QI/POP Rank
1USA China China Finland Italy Sweden Germany France China 1.32 5.6 40 Sweden 1
2Germany Italy Germany Slovak Rep. Switzer land Slovak Rep. UK UK India 1.13 9.9 6 5 Switzerland 2
3Russian Fed. Spain Sweden Uruguay Spain Switzerland USA Germany USA 304.060 Germany 3
4UK Japan France Netherlands Hungary C zech Rep. France China Indonesia 228.250 Czech Rep. 4
5France Germany UK Sweden Czech Rep. Bulgaria Japan Romania Brazil 19 1.97 0 Italy 5
6Korea, Rep. UK USA Czech Rep. Singapore Hungar y Russian Fed. Korea, Rep. Pakistan 16 6. 04 0 UK 6
7Netherlands India India Switzerland Israel Portugal Korea, Rep. Japan Rus sian Fed. 141. 80 0 Netherlands 7
8Japan USA Spain Ireland Netherlands Chile Australia,NZ Italy Japan 127. 7 0 4 Finland 8
9China France Chile Singapore Bulgaria Serbia Italy Australia,NZ Mexico 106.350 Slovak Rep. 9
10 Italy Korea, Rep. Czech Rep. Austria UK Denmark China Poland Germany 82.140 France 10
11 Canada Russian Fed. Brazil Denmark Slovak Rep. Finland Netherlands USA Egypt 81.527 Spain 11
12 Czech Rep. Brazil Switzerland Hungary Greece Norway Swit zerland Spain Turkey 73.914 Korea, Rep. 12
13 Australia,NZ Netherlands Hungary Norway Germany Belgium Czech Rep. Russian Fed. Iran 71.96 0 Hungary 13
14 Mexico Turkey Portugal Bulgaria Sweden Ireland Canada India Thailand 67. 3 9 0 Japan 14
15 Spain Switzer land Korea, Rep. UK Croatia Greece South Africa Czech Rep. France 62.050 Australia,NZ 15
16 Poland Poland Netherlands Australia,NZ Austria Singapore Hungar y Netherlands UK 61.39 9 Austria 16
17 Sweden Romania Malaysia Korea, Rep. Ireland Germany Spain Belgium Italy 59.850 USA 17
18 Brazil Canada Romania Germany Romania Netherlands Mexico Finland South Africa 48.690 Romania 18
19 Finland Hungary Bulgaria Serbia Japan France Poland Sweden Korea, Rep. 48.610 China 19
20 Hungary Czech Rep. Slovak Rep. Canada Portugal UK Finland Switzerland Spain 45.56 8 Poland 20
21 Turkey Australia,NZ Indonesia Portugal Korea, Rep. Austria Slovak Rep. Austria Argentina 39. 88 0 Denmark 21
22 Switzerland Argentina Greece France Belgium Croatia Brazil Hungary Kenya 38.53 0 Singapore 22
23 Thailand Iran South Africa Poland Australia,NZ Romania India Slovak Rep. Poland 38 .123 Ireland 23
24 Slovak Rep. Greece Belgium Spain France Spain Sweden Brazil Canada 32. 307 Belgium 24
25 South Africa Israel Poland Romania Finland Malaysia Austria Serbia Venezuela 27. 9 40 Russian Fed. 25
26 Austria Malaysia Turkey Croatia Nor way Israel Turkey South Africa Malaysia 26.990 Portugal 26
27 Argentina Indonesia Canada Russian Fe d. Canada Korea, Rep. Denmark Canada Korea, DPR 23.860 Nor way 27
28 Romania Sweden Japan Italy Uruguay Kazakhstan Romania Turkey Romania 21.510 Canada 28
29 Denmark Bulgaria Serbia Greece Poland Canada Singapore Bulgaria Australia 21.370 Bulgaria 29
30 Ireland Thailand Russian Fed. Belgium Denmark Poland Argentina Portugal Cameroon 18.900 India 30
31 Singapore Portugal Denmark USA Serbia South Africa Portugal Norway Netherlands 16.440 South Africa 31
32 India Mexico Austria South Africa Chile Uruguay Thailand Argentina Chile 16.2 97 Brazil 32
33 Bulgaria Belgium Finland Argentina Malaysia Domin. Rep. Malaysia Denmark Kazakhstan 15. 670 Greece 33
34 Uruguay Singapore Italy Japan Argentina Turkey Indonesia Mexico Greece 11.2 40 Turkey 34
35 Portugal Austria Thailand Malaysia Turkey USA Bulgaria Iran Belgium 10.70 0 Serbia 35
36 Malaysia Chile Norway Thailand China Italy Norway Thailand Portugal 10.620 Argentina 36
37 Norway South Africa Kazakhstan Turkey Korea, DPR Brazil Belgium Ireland Czech Rep. 10.43 0 Israel 37
38 Serbia Korea, DPR Singapore Mexico Kazakhstan Argentina Greece Malaysia Hungary 10.0 40 Mexico 38
39 Greece Slovak Rep. Ireland Chile Russian Fed. Thailand Egypt Egypt Domin. Rep. 9.8 40 Malaysia 39
40 Belgium Croatia Argentina Brazil Iran China Ireland Indonesia Sweden 9. 22 0 Croatia 40
41 Indonesia Kazakhstan Croatia China USA Japan Uruguay Israel Austria 8.344 Uruguay 41
42 Chile Pakistan Israel Indonesia Thailand Australia,NZ Chile Greece Switzerland 7. 6 3 0 Thailand 42
Country Rankings based on different criteria
35
Ulrich Harmes-Liedtke, Juan José Oteiza Di Matteo
DAC ODA non ODA
Rank CMCs ISO9001 TAB CMCs/Pop ISO9001/
Pop
TAB/ Pop K&S Com-
parison
TC Participa-
tion
Population (thousands) QI/POP Rank
43 Croatia Ireland Australia,NZ Egypt South Africa Russian Fed. Israel Kenya Bulgaria 7.620 Egypt 43
44 Egypt Serbia Domin. Rep. India Brazil Indonesia Serbia Croatia Serbia 7. 35 0 Indonesia 44
45 Pakistan Finland Egypt Pakistan Mexico India Croatia Pakistan Israel 7.3 10 Iran 45
46 Cameroon Egypt Pakistan Cameroon India Venezuela Kazakhstan Singapore Denmark 5.500 Pakistan 46
47 Domin. Re p. Norway Venezuela Domin. Rep. Indonesia Egypt Venezuela Chile Slovak Rep. 5.410 Chile 47
48 Iran Denmark Uruguay Iran Egypt Pakistan Kenya Korea, DPR Finland 5.244 Kenya 48
49 Israel Urugay Iran Israel Venezuela Iran Pakistan Kazakhstan Singapore 4.840 Kazakhstan 49
50 Kazakhstan Venezuela Mexico Kazakhstan Pakistan Me xico Iran Uruguay Norway 4.770 Korea, DPR 50
51 Kenya Kenya Kenya Kenya Kenya Kenya Domin. Rep. Cameroon Ireland 4.460 Cameroon 51
52 Korea, DPR Do min. Rep. Korea, DPR Korea, DPR Korea, DPR Korea, DPR Cameroon Venezuela Croatia 4.430 Venezuela 52
53 Venezuela Cameroon Cameroon Venezuela Cameroon Cameroon Korea, DPR Domin. R ep. Uruguay 3.33 0 Domin. Rep. 53
36
Measurement of Quality Infrastructure
Country Member-
ship
DAC ODA non
ODA
CMCs
(Jan.
2010)
Key
Comp.
Suppl
Comp
(Jan.
2010)
ISO9001
(2008)
Tech
Comm
(Jan.
2010)
TAB ( Jan.
2010)
GCI
2009-
2010
Expo rt s
USD
(2009)
PIB per
cap P PA
(2008)
Argentina 7UMI 277 65 16 8812 319 154 3,91 58 ,87 14331
Australia,NZ 8 x 493 226 39 10001 625 71 5,065 187,7 5 34241
Austria 8 x 331 90 23 4272 506 2 59 5,13 13 9, 8 0 3 8153
Belgium 8 x 97 32 10 4 875 537 436 5,09 29 6,10 34506
Brazil 8UMI 435 111 21 14539 435 751 4,23 15 8, 90 10 312
Bulgaria 6 x x 191 29 17 5323 351 551 4,02 16, 23 12398
Cameroon 4LMI 00012 31 03,5 3,41 2 215
Canada 8 x 534 153 23 1050 6 376 391 5,33 298,50 37577
Chile 5UMI 49 1 8 4103 105 943 4,7 48,85 14874
China 8LMI 730 206 25 224616 706 4170 4,74 1194 , 00 5962
Croatia 6UMI 45 12 22302 188 11 6 4,03 10,05 1910 2
Czech Rep. 8 x 503 139 42 10089 581 857 4,67 106,40 247 07
Denmark 8 x 211 72 24 1574 308 263 5,46 88,87 36591
Domin. Re p. 3LMI 0 0 0 63 0 61 3,75 5,37 82 16
Egypt 8LMI 23 25 81944 247 52 4,04 22,91 5 416
Finland 8 x 431 91 43 1975 530 250 5 ,43 57,8 8 35892
France 8 x 980 287 60 23837 7 19 2050 5,13 456,80 34044
Germany 8 x 1537 407 114 48324 712 32 12 5,37 11 87, 0 0 3 56 13
Greece 8 x 107 29 10 6747 197 452 4,04 18 ,6 4 29356
Hungary 6 x 385 137 16 10187 487 681 4,22 78,61 1932 5
India 8LMI 200 111 16 37958 594 1217 4,3 155, 00 2 972
Indonesia 8LMI 83 41 65713 219 487 4,26 11 5, 6 0 3975
Iran 6LMI 0 0 2 7844 299 11 070,16 10791
Ireland 8 x 211 21 32 237 251 180 4,84 1 07, 3 0 4 4195
Israel 7 0 11 46438 19 9 107 4,8 44,35 27541
Italy 8 x 593 178 54 118 3 09 655 240 4,31 3 69,0 0 30759
Japan 8 x 735 284 44 62746 668 379 5,37 516,3 0 34099
Values of main indicators ordered by countries
37
Ulrich Harmes-Liedtke, Juan José Oteiza Di Matteo
Country Member-
ship
DAC ODA non
ODA
CMCs
(Jan.
2010)
Key
Comp.
Suppl
Comp
(Jan.
2010)
ISO9001
(2008)
Tech
Comm
(Jan.
2010)
TAB ( Jan.
2010)
GCI
2009-
2010
Expo rt s
USD
(2009)
PIB per
cap P PA
(2008)
Kazakhstan 4UMI 0 5 5 2295 70 2 01 4,08 41,6 4 11318
Kenya 5OLI 0 1 4 257 19 0 03,67 4,48 1590
Korea, DPR 4OLI 0 0 0 3543 94 0 0 2,06 0
Korea, Rep. 8 x 934 234 42 23 036 696 654 5355,10 2 7937
Malaysia 7UMI 155 44 10 6267 247 558 4,87 15 6, 40 14217
Mexico 7UMI 479 115 26 4990 303 04 ,19 223,60 14 495
Netherlands 8 x 824 162 50 13597 573 640 5,32 3 97, 6 0 40 857
Norway 8 x 15 0 34 10 1666 334 227 5,17 12 2,0 0 58129
Pakistan 8OLI 0 2 2 2268 145 33 3,58 17, 87 26 44
Poland 8 x 461 111 26 10965 622 43 0 4,33 13 4, 70 1762 5
Portugal 8 x 173 65 95128 342 675 4,4 41,43 23084
Romania 8 x 225 70 19 10737 700 551 4 ,11 38 ,10 1406 6
Russian Fed. 6 x 1413 229 51 16 051 6 03 354 4,15 295,60 16 139
Serbia 5UMI 134 14 12091 430 373 3,77 8,82 1145 7
Singapore 7 x 208 66 22 4526 138 193 5, 55 245,00 49277
Slovak Rep. 8 x 346 109 24 3476 438 530 4, 31 45,05 22065
South Africa 8UMI 345 132 30 3792 395 447 4,34 67, 93 10108
Spain 8 x 478 119 32 6873 0 605 100 8 4,59 2 15, 70 31955
Sweden 8 x 446 94 30 537 7 528 2527 5,51 132, 8 0 37387
Switzerland 8 x 361 13 2 55 11724 521 706 5,6 19 0,10 42539
Thailand 7LMI 356 53 16 5275 252 238 4,56 136 , 60 7702
Turkey 8UMI 380 78 25 13217 363 406 4 ,16 111,10 139 20
UK 8 x 1220 315 68 41150 7 14 194 6 5,19 351,30 35445
Uruguay 4UMI 189 12 8999 56 21 4 ,1 6,32 1274 7
USA 8 x 2260 314 57 3240 0 612 16 01 5,59 9 9 7, 70 467 16
Venezuela 4UMI 0 2 3 448 029 3,48 51,9 9 128 06
38
Measurement of Quality Infrastructure
Canavos, George, 1993, Probabildad y estadística. Aplicaciones y métodos, Mc Graw-Hill.
Guasch, J. Luis, 2007, Quality Systems and Standards for a Competitive Edge, The International Bank for Recon-
struction and Development/The World Bank.
ITC, International Trade Centre, World Trade Organization WTO y United Nations Conference on Trade and
Development UNCTAD, 2005, Innovations in Export Strategy.
Sanetra, Clemens, 2007, The answer to the global quality challenge: A national quality infrastructure, PTB, OAS and
SIM.
Schwab, Klaus, 2009, The Global Competitiveness Report 2009–2010, World Economic Forum, Geneva.
UNCTAD, United Nations Conference on Trade and Development, 2007, The Least Developed Countries Report
2007, New York and Geneva.
World Trade Organization, 2005, World Trade Report 2005. Exploring links between trade standards and the WTO.
5 BIBLIOGRAPHY
39
Ulrich Harmes-Liedtke, Juan José Oteiza Di Matteo
Physikalisch
Technische
Bundesanstalt
Braunschweig und Berlin
Physikalisch
Technische
Bundesanstalt
Braunschweig und Berlin
Physikalisch-Technische Bundesanstalt
Braunschweig und Berlin
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Braunschweig und Berlin
Physikalisch
Technische
Bundesanstalt
Braunschweig und Berlin
Physikalisch
Technische
Bundesanstalt
Braunschweig und Berlin
Physikalisch-Technische Bundesanstalt
Braunschweig und Berlin
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