Chapter 13 Innovation Statistics

Giuliana Battisti and Paul Stoneman

What is innovation and why do we measure it?

Why do we not just have one measure of innovation?

What are the existing sources available, and how accurate are they?

What is missing from innovation statistics?

How far back in time can we measure innovation?

13.1 Introduction

The definition we use is from the OECD’s glossary of statistical terms.

innovation
The implementation of a new or significantly improved product (good or service), or process, a new marketing method, or a new organisational method in business practices, workplace organisation or external relations. This new and/or improved product or process differs significantly from the unit’s previous products or processes, and has been made available to potential users (product) or brought into use by the unit (process).

On 1 October 1963, Harold Wilson, at that time the leader of the UK’s political opposition, made a famous speech at the Labour Party conference in Scarborough. For the first time a leading national politician chose to focus on the role of innovation as the engine of growth for the economy. The British people were, he said, “accepting as part of their everyday life things which would have been dismissed as science fiction a few years ago”.

He went on: “This scientific revolution” he said, “is making it physically possible … to achieve for the whole people better living standards than those enjoyed by tiny privileged classes in previous epochs”.

A year later, Wilson’s vision of how new ideas could become products and services that improved everyday life – what he called the “white heat of technology” – had helped him to become prime minister, a job he held until 1970.

Today we more easily accept that innovation drives long-run economic growth, nationally and globally. It is also a prime determinant of the competitiveness of nations (and thus export performance), the competitiveness of firms (and thus firm output growth, employment and profits), and the enhancement of our wellbeing.

As such, innovation is at least as important as any other production activity, and has to be fully understood, monitored, managed and measured. However, we now take a much wider view of what innovation encompasses than we did when Wilson made his speech. Innovation can also mean changes in management methods and techniques, product design and, in many sectors, changes in product aesthetics too.

Innovation plays a role in economic growth and development that is too important for it to be left to occur by chance. Policymakers need to identify where to intervene usefully in the innovation process, and they can do that only if they gather statistics on the ways firms innovate, and how successful they have been.

William Baumol, an economist who specialised in innovation, put it like this:

…firms cannot afford to leave innovation to chance … [they] are forced by market pressures to support innovation activity systematically … The result is a ferocious arms race among firms in the most rapidly evolving sectors of the economy, with innovation as the prime weapon.1

To create policies to encourage innovation, we first have to measure it, and its effect. This is problematic. It is difficult to define innovation, but even harder to measure it – not least because what we measure depends on what we define.

13.2 What is innovation?

The simplest definition of innovation that we could have used is that it is “the successful exploitation of new ideas”, the definition used by the Innovation Unit of the Department for Business, Innovation and Skills in the UK. We use this narrow definition to begin our investigation in section 13.3.

The use of the term in modern economics goes back to the work of Joseph Schumpeter, the first economist to analyse in detail the impact of innovation on technological change and growth. Later we want to learn about the effectiveness of innovation policy, so we need to understand, as Schumpeter did, that innovation has three stages. Before implementation there must be an idea, and after implementation there is the value that the idea generates.

Schumpeter’s ideas are set out in:

Schumpeter JA (1934), The Theory of Economic Development: an Inquiry into Profits, Capital, Credit, Interest and the Business Cycle, New Brunswick, NJ: Transaction

He considered that innovation encompassed new products, new processes, new materials, new management methods and new markets, and involved three interrelated stages:

  1. Invention: the generation of new ideas
  2. Innovation: the translation of new ideas into new products, and production and business processes
  3. Diffusion: the spread of the latter across their potential uses.

We will call Schumpeter’s three-step analysis the wider concept of innovation, and we deal with that in sections 13.4, 13.5 and 13.6.

Note that both definitions use the phrase “new ideas”. There are three main concepts of newness:

Instinctively we think of innovation as something that is new to the world. That would be a very incomplete picture of the innovative activity we want to quantify. Most profit-generating innovations in firms or households will not even be new to the industry in which they are applied, let alone new to the world.

We will start with the challenges of the measurement of the narrow concept of innovation and look at the available statistics and what they show.

13.3 Measuring narrow innovation

13.3.1 What we include, and why

The definition and measurement of the narrow concept of innovation has been largely guided to date by what is known as the Oslo Manual. The latest version, published in 2018, defines business innovation as

…a new or improved product or business process (or combination thereof) that differs significantly from the firm’s previous products or business processes and that has been introduced on the market or brought into use by the firm.

More formally entitled Guidelines for Collecting and Interpreting Innovation Data, the “Oslo Manual” was first published by the Organisation for Economic Cooperation and Development (OECD) in 1992. The 1992 edition was mainly concerned with measuring (technological) innovation within the business enterprise sector and was restricted to manufacturing.

The second and third editions broadened the scope to market services and the concept of innovation to include marketing and organisational innovations. We are now on the fourth (2018) edition.

Innovation statistics compiled to date mostly use the guidelines in the 2005 manual. This may change when the 2018 edition is employed.

This distinguishes between innovation as a process and innovation as an outcome. One may think of the innovation process as an (economic) activity that uses resources in order to generate innovation outcomes. This process itself may be studied in order to explore its productivity (output per unit of input), for example. Innovation as an outcome is essentially an attempt to measure the outcomes from the process, and it is these outcomes that the manual refers to as innovation. Both aspects are relevant to both the wide and narrow concepts of innovation. The distinction suggests that it may be advantageous to separate measures of innovation relating to inputs to the process from those relating to outputs from the process.

We can measure innovation at the macro (national or international) level or at the micro (industries, firms, households) level. But, when we do this, aspects of the 2018 Oslo Manual definition raise problems – most importantly, the number of changes that can be recorded as innovation.

In the guidelines, the minimum requirement for an innovation is that the product or business process must have one or more characteristics that are “significantly different” from those contained in the products or business processes previously offered by or used by the firm. These characteristics must be relevant to the firm or to external users. Product innovations must provide “significant improvements” to one or more characteristics or performance specifications.

There is a very long list of relevant functional characteristics which includes:

That’s not all. An improvement to or addition of a new function can also be combined with a loss of other functions, or a decline in other performance specifications. So poorer quality, cheaper products can now be counted as innovations.

Note also that “significant” is not explicitly defined. An obvious gauge of significance would be market impact – an innovation that makes a large market impact would be considered as more significant than one that fails.

But the Oslo definition focuses on the process, and that would be an outcome. So a change does not need to be a commercial, financial, or strategic success, either at the time of measurement, or ever! A product change can fail commercially, or a business process change may require more time to meet its objectives. Around 40% of product innovations fail to deliver commercial success. By this definition, innovation does not necessarily improve the market position or financial performance of the firm, even if users benefit from it.

Nor does the definition of an innovation require it to have a positive value for society or consumers (outcomes, again), as distinct from the firm. An innovation can lead to a significant boost in the financial performance of the firm while providing fewer benefits to consumers than other offerings from the same firm, or its competitors. This means an innovation, by this definition, can create safety, health or environmental problems.

13.3.2 Measuring innovation using surveys

Although the Oslo Manual definition of narrow innovation is far from perfect, it is the basis of Community Innovation Surveys (CIS). They are a series of Innovation Surveys mainly undertaken every two years (or sometimes three yearly or annually) by National Statistical Offices in all the EU member states using a harmonised approach (with countries, where desired, making national additions). In some countries, participation in the surveys is compulsory; in others, it is voluntary.

Dive into the most recent Community Innovation Survey data.

In the UK, the CIS is called the UK Innovation Survey (UKIS). Participation is voluntary, but samples tend to be large. In 2019, the sample was nearly 31,000 UK enterprises with ten or more employees, with responses from around 14,000 businesses. In addition to questions relating to R&D activity, patenting activity, barriers to innovation and sources of information about innovations, the survey asks, crucially, whether firms are innovation-active, and whether the new products and processes are new to the firm, or the market, and first in the country, Europe, or the world.

UK Innovation Survey 2019 provides the results from the latest round of the UK survey.

innovation-active firm
A firm that has had innovation activities during the period under review, including those with ongoing and abandoned activities. In other words, firms that have had innovation activities during the period under review, regardless of whether the activity resulted in the implementation of an innovation.

The 2019 results for the UK suggest that:

Figure 13.1 Percentage of businesses engaging in innovation by activity, UK, 2008 to 2018

Percentage of businesses engaging in innovation by activity, UK, 2008 to 2018

In these surveys, information on firm size is usually collected, but not other firm characteristics. In some countries, researchers may be given privileged secure access to anonymised company-level data so that CIS data can be combined with Census of Production data. When this happens, we can analyse the relationship between innovation, firm characteristics and innovation performance.

For cross referencing in the UK, it is possible to merge the information from the UKIS with the information contained in micro datasets on turnover, purchases, employment costs, capital expenditure and stocks.

One finding from the CIS data is that firms that undertake one innovative activity also tend to undertake others. Two major clusters of innovations tend to be undertaken jointly:

The evidence also indicates that the sample of firms can be separated into three clusters.

The smallest cluster undertakes both sets extensively, and the second (a slightly larger group), undertakes both to a limited degree, whereas the largest group does not innovate in either category to any degree.

This suggests not only complementarity, but also that wide and technological innovation are not substitutes, and, most importantly, that businesses that are innovative in one dimension tend to be innovative in all dimensions. There are agile organisations that realign not only to deliver innovation but importantly, extract value from it. The data patterns also indicate that the innovative performance of firms is heavily skewed, with a large part of the UK companies engaging only marginally in the innovation process.

ONS Resource

A further source of data on the uptake of management practices in British production and services industries is the recent Management and Expectations Survey (MES) carried out in 2017 and developed as a follow up of the 2016 pilot Management Practice Survey (MPS).

The MES questionnaire covers a slightly modified and broader set of questions than the MPS and the UKIS, and it was designed to align to the Management and Organisational Practice Survey (MOPS) conducted by the US Census Bureau.

Despite being one of the few surveys on the adoption of management practices, it contains limited information on either narrow or wide innovations and general company characteristics.

Outside the EU, there is survey data for many other countries. This data is collected and harmonised by international organisations.

The United Nations Educational, Scientific and Cultural Organization (UNESCO) Institute for Statistics provides free access to internationally comparable data on science, technology and innovation. It is the only global database of cross-nationally comparable indicators on innovation.

The latest report, compiled in 2015, examined the innovation process of countries in two groups of World Bank classification of level of income: high-income, and low- and middle-income. The survey gathered data from 71 countries, including nine in Africa, in order to produce a range of basic innovation indicators to inform policies at national and international levels.

The 2015 UNESCO main results can be found at Results of the 2015 UIS Innovation Data Collection.

Highlights from the 2015 survey:

In high-income countries:

In low- and middle-income countries:

13.3.3 Using product launch data

Although CIS data are comprehensive, they are problematic for three reasons:

A particularly informative set of data is provided by Paul Stoneman’s book on launches of new creative products such as books and recorded music. For example, in 2006, 33,524 new music albums were launched. In publishing it was estimated that over 200,000 new titles were published in the UK in 2005 (growth of about 12.5% in the stock).

Stoneman P (2010), Soft Innovation: Economics, Product Aesthetics, and the Creative Industries, Oxford: Oxford University Press

Product launch information would seem particularly useful to address these problems. These include product launch data from government sources such as the Food and Drug Administration in the US and similar agencies elsewhere in the world, and product launch data from organisations such as those included in the Mintel New Products Database.

13.3.4 Defining successful innovation

In section 13.3.1 we argued that innovation might only be considered significant if it was a market success. For example, of the 33,524 new music albums launched in the UK in 2006, only 233 entered the top 40, and a US study estimated that despite huge numbers of new books being published, 205 books accounted for 84% of sales in a six-month period (and thus most books sold very few copies). This suggests there is much more innovation than successful innovation.

Recall the definition of innovation used by the Innovation Unit of the Department for Business, Innovation and Skills in the UK. It differs fundamentally from the Oslo Manual definition because it required the successful exploitation of new ideas.

The emphasis on success stresses the outputs, which the Oslo Manual definition does not mention. It emphasises that investment in innovation activities is of little economic relevance unless it successfully generates value. It also brings one closer to more recent definitions of innovations that are designed to reflect the contributions of investment in knowledge (or intangible) capital. In other words, innovations add to that capital only if they are successful.

How it’s done Measuring successful innovation

Giuliana Battisti and Paul Stoneman formalised this definition as the contribution of innovative activity to firm profit growth. This aims to capture the successful exploitation of new ideas.

This contribution is calculated using publicly available accounting data, for an unbalanced sample of 16,457 firms over the period 1988 to 2012 operating in 39 sectors and in 38 countries.

They found that, on average, the innovative activity is responsible for 5.15 percentage points of the company’s annual profit growth. The contribution of innovativeness to profit growth shows a very high variance across firms with significant differences within sectors, or countries, greater than differences across sectors, or countries.

You can investigate their methodology in their paper:

Battisti G, Stoneman P (2019), “Measuring the Innovativeness of Firms”, ESCOE Discussion paper No 19/2019, London, November

This approach has many similarities with the extensive literature on the growth of Multi Factor Productivity (MFP), as discussed in Chapter 6, which is often interpreted as a measure of innovative activity.

Total factor productivity measures how much output is produced per unit of input, including labour hours, the quality of labour and the impact of capital. It is the unexplained residual after the impact of these other factors is identified. It can be considered the “recipe” or the way in which the inputs are put together to make the output. So it is defined and calculated as the rate of growth of real value added that is not the result of increased capital and labour inputs.

Discovering a better recipe means more output for the same inputs and therefore higher MFP. Clearly this may be interpreted as successful innovation.

13.4 Measuring wider innovation using research and development

research and development (R&D)
Creative and systematic work undertaken in order to increase the stock of knowledge – including knowledge of humankind, culture and society – and to devise new applications of available knowledge. Data relating to research and development (R&D) has been collected for the longest period of time and very widely. It is now generally available for most economies, in some cases extending back to the 1960s, at both macro and micro levels.

The wider innovation concept encompasses all three stages of the Schumpeter trilogy: invention, innovation and diffusion. The first indicator is research and development (R&D) spending.

13.4.1 Measuring research and development

ONS Resource

In most countries, R&D data are collected by national statistical offices either annually or through innovation surveys. In the UK it is available at the ONS under Research and Development expenditure.

Data is also made available in comparative tables by several international organisations such as the OECD in its STAN database from 1987, or the World Bank in its Science and Technology databank, covering 264 countries.

As recommendations on accounting practice have changed over time, so the number of firms reporting R&D in their annual accounts has also been increasing, thereby making available an increasing amount of data at the firm level. Such data have been and sometimes are listed in scoreboards.

The 2019 edition of the EU Industrial R&D Investment Scoreboard covers the R&D activities of the 2,500 companies investing the largest sums in R&D in the world in 2018 and 2019 . In the past, the UK has also produced a local Scoreboard, but this was discontinued in 2010.

Guidelines on the collection of R&D data have been available from (and to a large degree followed by) most statistical agencies since 1963 when the OECD first published its guidelines. The latest edition of the guidelines says:

Research and experimental development (R&D) comprise creative and systematic work undertaken in order to increase the stock of knowledge – including knowledge of humankind culture and society – and to devise new applications of available knowledge.

Note that the definition covers both science and technology, and by including the phrase “knowledge of humankind, culture and society”, also includes the humanities and social sciences. The definition encompasses basic research (research with no particular application in view), applied research (research with a particular applied objective) and experimental development.

The Frascati Manual is a document that defines how we collect statistics about R&D. The Manual was prepared and published by the OECD.

13.4.2 GERD, BERD and other measures of R&D

gross expenditure on R&D (GERD)
Monetary value estimates of research and development performed and funded by business enterprise, higher education, government, UK Research and Innovation, and private non-profit organisations.

Data available usually includes total expenditure on R&D, labelled gross expenditure on R&D (GERD), which is often separated between civil and military. This expenditure is commonly also separated out between basic research, applied research and experimental development, at least in official statistics.

A further distinction generally made is that between the sectors funding R&D and the sectors performing R&D.

There are three main funding sources: business enterprises, government, and overseas sources (including international bodies such as the European Commission). In the UK, the main performers of R&D are business enterprises, government, including government departments and government-owned research establishments, and universities.

business enterprise R&D (BERD)
The component of GERD incurred by units belonging to the business enterprise sector.

The R&D performed and funded by business enterprises are usually given the acronym BERD, standing for business enterprise R&D data. It is collected regularly by statistical offices. Data is also collected on R&D performed by higher education (HERD), government, including UK Research and Innovation, R&D (GovERD), and private non-profit organisations (PNPRD). Business enterprises generally undertake more R&D than they fund, whereas governments fund more than they undertake. Figure 13.2 illustrates the different flows of research and development funding and performance in the UK in 2018.

Figure 13.2 Flows of research and development funding, UK, 2018

Flows of research and development funding, UK, 2018

We can use this data to compare R&D over time and across countries, but we must take care to use an appropriate price deflator. General price deflators such as the GDP deflator or the consumer price index would be unlikely to be appropriate.

In the UK, the Office for National Statistics (ONS) constructs a price deflator by weighting whole-economy materials and services input (producer) price indices together with a bespoke R&D labour cost price index. This labour cost price index is calculated using information on the labour employed in producing R&D coupled with gross hourly wage estimates for relevant occupations taken from the Annual Survey of Hours and Earnings to estimate a Laspeyres fixed-weight wage index.

International comparisons of effective R&D spends will also necessitate some correction for differences in the currency in which they are measured. The use of purchasing power parity is common and sensible.

In Figure 13.3, we illustrate some of the data on international patterns of R&D spending as a percentage of GDP in six economies.

Figure 13.3 GERD (Gross domestic expenditure on R&D) as a percentage of GDP in six countries, 2018

GERD (Gross domestic expenditure on R&D) as a percentage of GDP in six countries, 2018

Figure 13.3a Research and development spending as a percentage of GDP in selected countries, 2000–2018

Across the various countries on which data is available in 2017, the percentage of GDP spent on R&D fluctuated between 0.5% and 4.23%

Across the various countries on which data is available in 2017, the percentage of GDP spent on R&D fluctuated between 0.5% and 4.23%

Figure 13.3b Research and development spending as a percentage of GDP in selected countries, 2000–2018

Sweden, Germany and the US are among the countries that invest most in R&D relative to GDP

Sweden, Germany and the US are among the countries that invest most in R&D relative to GDP

Figure 13.3c Research and development spending as a percentage of GDP in selected countries, 2000–2018

Italy and Spain invest less in R&D as a % of GDP, though substantial differences remained within the EU.

Italy and Spain invest less in R&D as a % of GDP, though substantial differences remained within the EU.

Figure 13.3d Research and development spending as a percentage of GDP in selected countries, 2000–2018

The UK R&D spend was 1.68%, ranking 11th among all the then EU countries

The UK R&D spend was 1.68%, ranking 11th among all the then EU countries

We simplified this figure from a dataset of 20 countries that you can download from Eurostat.

The international patterns of R&D spending, as a percentage of GDP, in the 20 economies (measured in complete Eurostat dataset) include the following:

13.4.3 The limitations of R&D as an indicator

Despite the popularity and wide availability of R&D data, this indicator has a number of limitations as a measure of innovation, meaning we might underestimate total innovative activity and provide an unbalanced picture of overall innovative activity:

13.5 Measuring wider innovation using intellectual property rights

intellectual property rights (IPR)
The general term for the assignment of property rights through patents, copyrights and trademarks. These property rights allow the holder to exercise a monopoly on the use of the item for a specified period. These cover inventions, literary and artistic works, designs, and symbols, names and images used in commerce. They are protected by the law and provide exclusive rights to the inventors to earn recognition or financial benefit for a certain period of time.

The second indicator of the rate of “wide” innovation are counts of intellectual property rights (IPR) granted.

13.5.1 Types of IPR registration

Court enforceable IPR are formal methods designed to protect the rights of the originator, inventor, or pioneer of a technical invention (which is both new and inventive when the patent application is filed) by discouraging imitation.

They also provide a monopoly right to use the invention for economic and commercial advantage, allowing the inventor to recover the often high research and development costs sustained. By guaranteeing that invention is the property of the inventor, the latter is able to capture the economic value of their inventions and this creates the necessary incentive and environment for further innovations. IPR are legally enforceable, although the extent of their enforcement and protection may vary from country to country.2

The four main institutional formal arrangements that exist in most countries in order to reinforce IPR are patent, design right, copyright and trademark.

Patents

patent
A right granted by a government to an inventor in exchange for the publication of the invention; it entitles the inventor to prevent any third party from using the invention in any way, for an agreed period.

Patents protect new inventions and cover how things work, what they do, how they do it, what they are made of, and how they are made. A patent gives the owner the exclusive right to stop others from making, using or selling their invention. In many countries, only advances of an industrial nature can be patented, which causes them to be labelled utility patents. (In some other countries, such as the United States, there is also a form of patents called design patents that correspond to the design rights that offer protection elsewhere.)

To be granted a utility patent, an invention must be new, must involve an inventive step that is not obvious to someone with knowledge and experience in the subject, and must be capable of being made or used in some kind of industry. Patent counts are sometimes used to measure R&D productivity, but this has limitations as a measure. There will be many innovations that fall outside these restrictions and therefore are not patentable. Once granted, a patent must (in the UK) be renewed every year after the fifth and may then provide protection for up to twenty years from the date of the patent application.

Design rights

design rights
Granted by different jurisdictions as a form of formal intellectual property protecting ornamental properties, shapes, configurations, appearance, or pattern of an article of manufacture, and such designs must be both new and distinctive or original. Can be referred to as “design patents”, “community designs” or “registered designs”.

Design rights apply to intellectual property but relate to the physical appearance and shape of a product rather than the function or operation of that product, emphasising instead the appearance that results from the features of physical products or the way they look. They may, therefore, offer protection to product innovations that would not be covered by patents, for a fixed period up to 25 years; or they may provide additional protection to the design aspects of a new product over and above that offered by patents.

To qualify, the design must be new and individual in character; less than twelve months since it was first publicly disclosed; not dictated only by how the product works; and not include parts of complicated products that cannot be seen in normal use (for example, vehicle engine spare parts, or the parts inside a computer).

copyright
A form of intellectual property rights (IPR) that grants the creator of an original work (creative work) certain rights over that work for a limited period of time. The copyright holder has an exclusive right to reproduce their work in various forms such as printed publications or sound recordings.

Copyright applies to the expression of an idea, not to the idea itself or to any process by which that idea is embodied in a physical artefact. This is in contrast to the patent system, where the idea itself is protected and owned for a period by the patent holder. But copyright does not protect the names, designs, or functions of the items themselves.

Copyright is particularly applicable to new products in the creative industries and protects sound recordings, films, broadcasts, and original artistic, musical, dramatic, and literary works, including for example photographs, art sculptures, websites and web content, computer programs, plays, books, videos, databases, maps, and logos. For example, copyright is the mechanism that may be used to protect originators from the unauthorised downloading of music and films from the internet, or against copying from others’ originals. Software enjoys only copyright protection and not patent protection. In the UK, copyright is an automatic right and does not need to be applied for – though this is not true in all countries. This means it would be very difficult to discover the number of copyrights claimed.

Trademarks and trade secrets

trademark
Refers to words, symbols or other marks which are used by firms to distinguish their products or services from those offered by others. They protect inventions such as machines and machine parts; the design, shape or look of a product; things that are written, made or produced; and the name of a product, the logo or the brand.

A trademark is a sign that distinguishes a firm’s goods and services from those of other traders. A sign includes, for example, product or service names, logos, jingles and more generally words, pictures, or a combination of these.

Whereas patents require novelty and copyright requires originality, the counterpart for trademark is distinctiveness. While patents are not available for aesthetic innovations, such innovations may be trademarked.

Non-aesthetic innovations may also be trademarked. For example, a rock group can trademark its name, a product with a particular aesthetic, such as the iPad, can be trademarked, and particular products such as Mars bars and Crunchie bars may also be trademarked. To be registerable, the trademark must be distinctive for the goods and services for which application is made and must not be the same as, or similar to, any earlier marks on the register for the same or similar goods or services.

In the UK, a trademark does not have to be registered. An unregistered trademark provides certain rights under common law and the owner can use the trademark ™ symbol. However, it is easier to enforce rights if the mark is registered, which also enables use of the ® symbol to indicate registration.

13.5.2 Counting IPR

Counts of registered, hence formally recognised, IPR are an obvious measure of the extent of innovation. Of the various protections available, copyrights are not easily monitored, but patents, design rights and trademark registration data are more reliable and easily accessible. Hence, we focus on the latter group and report in Table 13.1 the number of applications and registration at the UK Intellectual Property Office (IPO) from 2011 to 2018.

Both the numbers of patent applications and grants have declined significantly since 2011, and especially in 2018. On the other hand, trademarks and designs have shown remarkably sustained growth. Trademark registrations have grown by nearly 250% and designs by about 700% since 2011, suggesting a clear shift in the nature of the typology of ideas being generated.


Intellectual property right

2011

2012

2013

2014

2015

2016

2017

2018
% change
2017–2018
Patents Applications 22,256 23,229 22,936 23,040 22,801 22,055 22,072 20,931 −5%
Publications 10,043 10,653 11,021 12,227 11,939 12,065 11,768 12,061 2%
Grants 7,173 6,864 5,235 4,986 5,464 5,602 6,311 5,982 −5%
Trademarks Applications 41,044 43,873 50,331 54,498 58,627 65,710 83,984 95,203 13%
Registrations 33,172 36,755 43,548 45,123 50,079 54,222 70,362 81,556 16%
Designs Applications 4,730 5,231 5,210 5,084 6,472 10,030 19,269 26,164 36%
Registrations 3,423 5,144 4,671 4,901 5,690 8,481 17,195 24,425 42%

Figure 13.4 Summary of all the UK registered IP rights: domestic and international registrations, 2011 to 2018

Summary of all the UK registered IP rights: domestic and international registrations, 2011 to 2018

Intellectual Property Office – Facts and Figures 2018: 2019

In the UK, the IPO holds databases that allow users to search by keyword, phrase, image or reference number. Existing patents, trademarks and designs can be identified, as can decisions on previous trademark applications. This is because access to searchable datasets of IPR is not just interesting for national statisticians. Inventors use them too:

The same information is important, too, for investors, government, intergovernmental organisations and for academic research. By exploring available details on individual patents registered, one can obtain very fine micro data sets such as the number of applications and grants by country of origin, patent sectoral classification and name of applicant.

How it’s done Protecting intellectual property with patents

In 2019 for the ninth straight time, Apple Inc. was ranked the world’s most valuable brand (worth $206 billion) by Forbes, a business magazine that compiles this statistic every year.

To protect its inventions and to deter competitors and imitators, the company has made extensive use of formal and informal intellectual property rights. Apple has consistently enforced secrecy until the launch of products and used complexity as a way to deter lookalike attempts.

The value of Apple’s products resides in both the function (protected by patents) and aesthetic design appearance (protected by registered designs, referred to as design patents in the US) to protect the latter.

In 2011, Apple started to claim its design patent over Samsung and began litigating against the South Korean company in technological patent infringement suits in a US court.

At the core of the case were three registered designs. The first registered design focused on the front flat clear face, the second on the bezel (the borders between a screen and a phone’s frame) and the third on the “ornamental design for a graphical user interface for a display screen or portion thereof”.

Apple argued that several of Samsung’s Android phones had systematically copied Apple’s innovative technology and products, features and designs, as prior to the introduction of the first generation iPhone (launched in 2007), there were no cellular phones that used a rectangular display screen that allowed for touch control interface.

The case was expanded to 50 lawsuits. The patent war between the two companies lasted more than seven years. In 2012, the American jury ruled in favour of Apple and ordered Samsung to pay Apple about $1.05 billion, the most significant design patent infringement award of all time.

By including design patents into its intellectual property portfolio, Apple was able to protect and capture the commercial exploitation of its innovation based upon its aesthetic appeal (rectangular shape multi-touch) rather than its functionality. However, a series of appeals followed up until 2018 when the order of dismissal of the first Apple v. Samsung case in the Northern District Court of California declared that the litigation was over, with both sides reaching an undisclosed out-of-court settlement.

13.5.3 IPR datasets

There is a wealth of data available on IPR, which can easily be searched through IP Offices’ ad hoc search engines and is freely accessible on their websites. For example:

International datasets have also been compiled, collating the information across the various national IP offices:

13.5.4 Using IPR to measure global innovation

Figure 13.5 illustrates a striking pattern in the number of patent applications across the world. Note the rapid increase of patent applications in China in the last decade in contrast to the relative decline in the US and Japan.

Figure 13.5 Intellectual Property Rights: Patent Applications for six large IP offices, 2004 to 2018

Intellectual Property Rights: Patent Applications for six large IP offices, 2004 to 2018

WIPO – IP Statistics Data Center, 2020

We could interpret this as the decline of innovation in two countries that dominated the adoption of process and technology improvement in the second half of the twentieth century, with China taking over. But the use of patent statistics as a measure of innovation has three problems:

Ariel Pakes and Margaret Simpson concluded that most patents turn out to be of little value, with rare big winners. They estimated a 1989 value of $6,000 for the average patent, with half of all the estimated patent rights accruing to between 5% and 10% of all patents. They also concluded that patents not renewed at or before five years had expired had almost no value.

Pakes A, Simpson M (1989), ‘Patent Renewal Data’, Brookings Papers on Economic Activity: Microeconomics, Volume 1989, pages 331–410

There is one major advantage of using patent data. IPR protection will often be sought by their owners for innovations being introduced into an economy from overseas. Importation is likely to be an important source of new products and processes and patent counts will reflect this more adequately than, for example, local R&D spend.

So IPR registration data has advantages and disadvantages as a measure of wider innovation activity. The data is widely available and there are long time series. But while R&D is clearly a measure of inputs into the innovation process, with IPR registration data the picture is less clear. Patents may be applied for at different stages in the innovation processes, sometimes early in that process, relative to the placing of an innovation upon the market, and sometimes late. Early application may be made, for example, to provide security for further development, while late application may provide greater secrecy.

Similarly, design rights may also be applied for at early or late stages, but since design will probably be an activity that is close to market, any application may be relatively late. By their nature, copyrights and trademarks will probably occur very close to or at the time of putting a product on the market.

Patent applications and design rights may best be considered as primarily a measure of intermediate outputs from the innovation process (those outputs reflecting increases in knowledge), with copyright and trademark counts being primarily a measure of innovations marketed rather than under development.

13.5.5 Informal methods of IPR protection rights

A further type of intellectual property rights is trade secrets (or confidentiality agreements) protected by the law via the enforcement of non-disclosure agreements (NDAs). NDAs are stipulated and signed by two parties who agree not to disclose to third parties the information agreed to be kept confidential. Employees, consultants and potential business partners may all sign NDAs that are not necessarily reported to or signed via institutional sources such as the IPO.

Should the information contained in the NDA be disclosed, it can be treated as breach of confidence and it is liable to legal action, although its protection can be weaker in countries such as the UK and the USA where trade secret law is part of common law.

There are some colourful examples of use of trade secrecy to protect IPR. One is the Coca-Cola secret formula whose only official written copy is allegedly kept in a bank vault in Atlanta. According to the legend (or possibly the marketing strategy) surrounding the trade secret, only two anonymous employees at any given time know the secret recipe and they are prohibited from taking the same plane in the event it crashes.

Another example is the trade secret of Colonel Harland Sanders’ secret blend of 11 herbs and spices used in Kentucky Fried Chicken (KFC). The recipe has been kept secret since July 1940 when Colonel Sanders, the founder of KFC, began selling fried chicken from his roadside restaurant in Corbin, Kentucky.

The use of informal intellectual property protection has been shown to be quite widespread and it is often preferred as the most effective protection mechanism for inventions. It is indeed cheaper, less time consuming and does not require complex applications.

From a statistical viewpoint, however, contrary to the formal protection methods, data on informal protection methods are neither systematically collected nor disclosed. Ad hoc surveys are the main source of information. Figure 13.6 reports the use of different approaches to formal and informal IP protection between 2014 and 2016 by the 13,194 enterprises present in the UK Innovation Survey (UKIS).

The results confirm the popularity of informal methods, although with differences across sectors. Knowledge intensive services tend to use more informal methods (lead time, complexity and secrecy) than high-tech manufacturing, while high-tech manufacturing uses more formal protection methods (trademarks and patents) than knowledge intensive services. It is worth pointing out that more than one type of informal and formal method can be used for a single product, indicating complementarities across protection methods.

  All Knowledge intensive services High tech manufacturing
Formal IP      
Patents 0.8 1.8 3.4
Design registration 0.8 1.6 1.6
Copyright 1.8 6.8 2.9
Trademarks 2.1 3.3 4.6
Informal IP      
Lead time advantages 0.9 3.3 2.3
Complexity of goods or services 2.0 6.4 5.7
Secrecy (including NDA) 2.5 8.7 5.5

Figure 13.6 Protection of innovation – percentages of firms that reported high use (more than 90%) of each protection method for their innovations, UK, 2014 to 2016

Protection of innovation – percentages of firms that reported high use (more than 90%) of each protection method for their innovations, UK, 2014 to 2016

13.6 Measuring wider innovation using diffusion statistics

Whether technological or non-technological, when an innovation appears upon a market for the first time, acceptance is often initially limited, with successful innovations then spreading more widely over time. This spreading process is known as innovation diffusion.

The third indicator of the rate of “wide” innovation is counts of innovation diffusion.

13.6.1 Measuring diffusion

The extent and speed of diffusion is a clear output measure of the innovativeness of an economy. In fact, of course, it is only as diffusion occurs that the benefits from innovation are realised. Diffusion can be analysed at country, sector, firm or at household level, depending on the nature of the innovation observed and the level of analysis. However, despite its importance, there are limited official statistics relating to the uptake of innovations. With few exceptions, ad hoc statistical surveys are the main sources of information.

Diffusion can take a very long time, sometimes decades, to spread across and within the population of eligible users.

To document the diffusion process fully, one needs to record, for each innovation, the number of users, and the depth of their use, from the date of first appearance of an innovation until diffusion is completed. Cross-sectional observations at a given point in time would provide only a partial view of the innovation diffusion process.

As an example of the need for a longitudinal view, the World Bank has published data on digital adoption across 180 developing and developed countries. Unfortunately, although interesting in showing the depth of penetration at a single point in time, it does not have the longitudinal dimension necessary to reflect the process of diffusion.

What data is available also tends to concentrate upon the number of users (the ‘inter’ dimension) rather than the depth of use (the ‘intra’ dimension). Diffusion data also has to be innovation specific, and it is often difficult to find agreement as to how to define the limits of any innovation being studied.

There are a few official statistics relating to technological and non-technological innovation diffusion:

ONS Resource

The ONS carried out the Management and Expectations Survey (MES) in partnership with the Economic Statistics Centre of Excellence (ESCoE) on the uptake of businesses’ management practices, as well as future expectations of turnover, employment, expenditure and capital investment growth. The survey covers 25,000 enterprises in the production and services industries in Great Britain. Data on the adoption of broader managerial innovations is also collected by the CIS survey.

None of the surveys asks for the date of first adoption of the innovation(s), and therefore one cannot derive the diffusion curves, but they do provide useful information of the depth and breadth of use across the population at each point in time.

For example, Figure 13.6 reports the diffusion of ICT in Great Britain measured by the percentage of households that used the internet between 1998 and 2019.

Figure 13.7 Household internet access in Great Britain, percentage, 1998 to 2019

Household internet access in Great Britain, percentage, 1998 to 2019

Office for National Statistics – Statistical bulletin: Internet access – households and individuals, Great Britain, August 2019 (the data for the period 1998 to 2004 covers the UK)

Typical of many diffusion processes, the diffusion pattern is one of a slow initial speed of diffusion that increases rapidly before gradually reaching the saturation point, when all the potential users have adopted the innovation. Also, characteristic of other diffusion examples (see Figure 13.9), it has taken nearly two decades for ICT to spread across the majority (93%) of eligible users.

ONS Resource

While Eurostat makes data publicly available only at sector, region and country level, ONS and the national statistical offices of other countries make them accessible at the finer business and household level, in an anonymised form, for academic and government research purposes under strict data management and non-disclosure conditions.

Anonymised data are made available through the ONS Secure Research Service and the UK Data Service (UKDS) and are available to any user, without charge, provided they have registered with the UKDS and they have undertaken the training to become an approved researcher.

13.6.2 Alternative sources of data on diffusion

There are a few additional sources to supplement the relatively limited data on diffusion. Government departments sometimes make available aggregate administrative data relevant to their competences. UK examples include:

Trade bodies also publish data for their respective industries for particular industries:

While trade body data is useful, it should be said that it is not always free to access. Further, while it is useful for identifying general aggregate trends at geographical, sector and national level, confidentiality considerations mean that such sources provide less detail for the microeconomic analysis of technology diffusion at household or firm level.

The Historical Cross Country Technology Adoption (HCCTAD) data set covers nearly two and a half centuries, from 1788 and to 2001, but is limited to the leading 23 industrialised countries in the world. CHAT is a data set with information on the adoption of over 100 technologies in more than 150 countries since 1800. The technologies that are covered relate primarily to durable goods, but include both consumer and producer durables, for example, mobile phones, TV sets, different steel production technologies, steamships, and motor ships. Such data is informative in comparing diffusion of single technologies across countries (see Figure 13.8 for an example) or to compare diffusion of various technologies within a single country (see Figure 13.9).

The diffusion curves for mobile phones in Figure 13.8 show the earlier adoption (date) and the faster speed of diffusion (steepness of the curve) of telephones uptake in the US. The adoption lag of the UK is interesting. Not much can be said about the height of the curves as they depend on the population size and hence the number of potential users. The population size is not accounted for in this exercise.

Figure 13.8 International diffusion of mobile phones in the US and UK, 1980 to 1999

International diffusion of mobile phones in the US and UK, 1980 to 1999

Historical Cross Country Technology Adoption Dataset, findings from these and other data sources upon diffusion

13.6.3 Patterns of diffusion

Paul Stoneman summarises evidence both on the extensive margin (the spreading across countries) and the intensive margin (spreading with countries) in this book:

Stoneman P (2002), The Economics of Technological Diffusion, Oxford: Blackwell

The figure of 47 years for adoption lag comes from the Comin and Hobijn study of 166 countries over the past two centuries. But there is wide variation across countries and across technologies.

adoption lag
The rate of pace at which new technologies spread and are exploited, with a lag referring to the length of time technologies remain unexploited. The adoption lag is therefore the difference in time taken to exploit a new technology after its release.
extensive margin
The extent to which innovation increases the number of products produced by each firm.
intensive margin
The extent to which innovation increases the value of each product produced.

For the majority of the innovations, diffusion curves are S-shaped while there are large cross-country and other differences in the adoption process. Figure 13.9 shows the diffusion of innovations in the UK in the last century. The rate of adoption can be affected by:

The Battisti and Stoneman study of UK metalworking and engineering firms shows that inter-firm diffusion (measured via the number of users) is dominant during the early stages of diffusion, while intra-firm diffusion (measured via the share of output produced using the new technology) becomes the main driving force in the last stages of the diffusion process. The findings also indicated that the number of users was an incomplete indicator of the overall usage of a new technology.

Battisti G, Stoneman P (2003), ‘Inter- and Intra-firm Effects in the Diffusion of New Process Technology’, Research Policy, Volume 32, Issue 9

A useful review of North-South models is given by:

Afonso O (2011), ‘R&D Direction and North-South Diffusion, Human Capital Growth and Wages’, Economics Research International, Review Article ID 401928

Using television as an example, Zhicun Gao and Clem Tisdell have explored patterns of the worldwide production of both black and white and colour TV sets. They show production shifting over time from the UK and US to Europe and Japan, and then to Taiwan, South Korea, Mexico, Italy, and Malaysia, all relatively low-income countries, and to China.

Gao Z, Tisdell C (2004), Television Production: Its Changing Location, the Product Cycle and China. Working Paper 26, Brisbane School of Economics, University of Queensland

Figure 13.9 The diffusion of innovations in the UK, 1900 to 1999

The diffusion of innovations in the UK, 1900 to 1999

13.7 Measuring innovation using alternative indicators

13.7.1 Prices

Surprisingly little use of pricing data has been used to illustrate where prices are falling over time because of innovation. Conceptually, allowing for quality change in the measurement of price change is a long-established practice (see Chapter 1) at aggregate level and there are well-established techniques to calculate such adjustments, although their use is not widespread. The same techniques can be used to measure the effects of quality change on the prices of individual products. Construction of hedonic price indices, for example, indicates how product prices have fallen as the result of product innovation improving quality per unit price. This has been done widely for personal computers, laptops, digital cameras, and other electronic goods, but is less common to date in other areas.

13.7.2 Scoreboards

A different approach is to consider jointly many indicators in what are known as scoreboards. They are widely used by government and international organisations for benchmarking innovation performance, and to identify areas of strengths and weaknesses for policy intervention. Examples include:

Scoreboards of this kind have the advantage of presenting a range of information in a convenient form. The difficulty is to know how much weight to give to the individual indicators, which may well be moving in diverse directions, to draw out the overall story. The European Commission Scoreboard attempts to give some help here by calculating a Summary Innovation Index for each Member State, giving equal weight to each of the available indicators. But such a weighting scheme is necessarily arbitrary.

13.8 Conclusion

Innovation is the engine of growth. We have identified wide (new to the individual economic unit) and narrow (new to the country) concepts of innovation and also differentiated between the process of innovation and innovation as an output of that process.

One of the significant problems in measuring innovation is that it requires an understanding of what needs to be measured and awareness of what can be reliably measured. Issues arise in this area when measuring business innovation, as more quantitative measures of innovation activities are more difficult to capture. Innovation and digitalisation are playing an increasingly important role, emphasising the need to create a rich, varied dataset that can be compared internationally.

There exists a plethora of micro and macro data on innovation accessible via national statistical offices, international organisations, intellectual property offices, firm level accounts and diverse other sources. Such data are widely used not only to measure the innovative effort and output of companies and countries worldwide, but also to explore the emergence of new technologies. Historically, such data have been one of the main inputs driving government innovation policies.

It is clear however that although there is wide availability of data on the level of activity in the innovation process (such as R&D data and data on IPR), there is much less data on the output from the innovation process such as the extent of the uptake of technological innovations by final users (either households or companies) or the depth of use by the adopters. Most importantly, there is less data on the benefits of uptake and depth of use, as it is only when ideas and innovations are used that the benefits from innovation are realised. Although Innovation Surveys have yielded much on this issue, these surveys have their limits and could be further extended.

13.9 Further reading

Notes

  1. Baumol WJ (2002), The Free Market Innovation Machine, Princeton, NJ: Princeton University Press 

  2. WTO | Understanding the WTO - Intellectual property: protection and enforcement 

  3. Comin DA, Hobijn B, (2010), ‘An Exploration of Technology Diffusion’, American Economic Review, Volume 100, Issue 5