Environmental Policy Stringency and Technological ... · Environmental Policy Stringency and...

Environmental Policy Stringency and Technological Innovation:

Evidence from Patent Counts

by

Ivan Hascic‡, Nick Johnstone

‡ and Christian Michel

†

May 7th, 2008

Abstract

This paper examines the impact of public environmental policy, as reflected in expenditures on

pollution abatement and control, on innovations in environment-related technology. The analysis is

conducted using patent data for a panel of 16 countries between 1985 and 2004. It is found that

there are important differences in innovation effects of resources spent in the public vs. private

sector and resources spent on pollution control activities vs. directly on R&D. These results are

broadly confirmed with a subsequent analysis on a broader cross-section of 33 countries over the

period 2001-2006, using an alternative measure of environmental policy stringency.

JEL codes: O31; O38; Q55; Q58

Keywords: Environmental Policy; Technological Innovation; Patents

‡ [email protected], [email protected] Empirical Policy Analysis Unit, OECD Environment

Directorate, 2 rue André Pascale, 75775 Paris Cedex 16, France

† Department of Economics, Oxford University, Manor Road, Oxford, United Kingdom

mailto:[email protected]

mailto:[email protected]

1

1. Introduction

There is currently much interest in the role of public policy in inducing innovations in technologies

which help reduce environmental impacts of economic activity. In many industrialized countries,

significant progress has been achieved during the past several decades on this front. For example,

emissions of pollutants into air and water have been greatly reduced1 and some advances have been

achieved in waste management.2 Most likely, this has been achieved due to structural changes in

economic activity (e.g., less emission-intensive production such as coal fired power plants), input

substitution (e.g., using coal with lower sulphur content), as well as via technological

improvements (incl. end-of-pipe solutions such as scrubbers, or production process innovations

such as fluidized bed combustion).

Understanding the factors that have determined this process is important for several

reasons. First, despite significant progress achieved to date, air and water pollution remains an

important public policy issue due its negative impacts on human health (see e.g., Cohen et al. 2005)

and ecosystem functions (see e.g., Islam and Tanaka 2004 and Lorenz 1995). Moreover, further

emissions reductions will require action on the part of more diffuse sources of pollution and may

therefore be more difficult to achieve, as their identification and measurement are complicated.

Finally, while emissions of many “traditional” pollutants are currently more-or-less controlled, new

“emerging” pollutants may become relatively more important in the future. In this context,

technological innovation is important because it allows society to further reduce environmental

impacts or to achieve a given environmental goal at lesser cost (see e.g., Kneese and Schultze

1977).

1 Between 1990 and 2005, emissions of SOx and NOx have fallen by 72% and 33% respectively in the

European Union (EU15) and 37% and 26% in the US. In some OECD countries emissions have actually

increased, notably in Australia and New Zealand with 25%-58% increase in emissions. Emissions causing

increased levels of water pollution have also been reduced in many countries. For example, the proportion of

population connected to public wastewater treatment plants has increased from 46% to 68% in OECD

countries during the last 25 years. However, enormous differences remain across countries – while as much

as 98% of population is connected in the Netherlands and the UK, the share is only 35% in Mexico and

Turkey (OECD 2007a). 2 Between 1990 and 2005, the volume of municipal waste generated per capita has remained stable in the US

(750 kg), had dropped slightly in Japan (from 410 to 400 kg), and has increased sharply in the European

Union (EU15) (from 430 to 570 kg) (OECD 2007a).

2

In the last several decades, OECD countries have introduced a number of policy measures

with the objectives to reduce environmental impacts of economic activity. However, it is difficult

to predict the effect of such policies on the pattern of technological innovation. While private (firm-

level) incentives to environment-friendly innovations may play some role3, it is public policy that

often plays the pivotal role in creating demand for technological innovation in environment-related

technologies, although its impact may vary across countries, pollutants, and over time.

In 1932, John Hicks observed that a change in the relative prices of factors of production

will motivate firms to invent new production methods in order to economise the use of a factor

which has become relatively expensive. This idea, originally developed in the context of labour

economics, came to be known as the “induced innovation hypothesis”. Applied to the public policy

framework, this implies that if governments could affect relative input prices, or otherwise change

the opportunity costs associated with the use of environmental resources, firms‟ incentives to seek

improvements in production technology would be increased. Indeed, since markets often fail to put

a price on environmental resources, the price of many environmental assets is to a large extent

formed by government regulation. Depending on the stringency of a regulation, the change in

opportunity costs of pollution then translates into increased cost of some factors of production.

Since this effect is unobservable to a researcher, pollution abatement and control expenditure

(PACE) can serve as an imperfect proxy for the changes in opportunity costs involved.

PACE has been used to examine the links between environmental regulation and

innovation in two distinct manners. In one case, the focus has been on the effects of PACE

expenditures on (plant-, sector-, or country-level) differences in productivity growth by examining

whether a given level of PACE has more or less greater impact on productivity (e.g., Gray and

Shadbegian 2003; Morgenstern, Pizer and Shih 2001; Jorgenson and Wilcoxen 1990; Gollop and

Roberts 1983; see also Jaffe et al. 1995 and papers cited therein). The basic question is whether, the

impact of a given level of PACE on productivity is more or less than unity. For instance, some

investments targeted at reducing environmental impacts may increase (or decrease) the efficiency

3 For instance, recycling of secondary materials to reduce input costs, consumer demand for „defensive‟

measures, etc.

3

associated with the use of other factors of production in production more generally (see Labonne

and Johnstone 2007 for discussion on this issue; see also Morgenstern, Pizer and Shih 2001).

In the second case, the focus has been on the effects of PACE on one aspect of productivity

– notably technological innovation, using patent data (e.g., Popp 2003; Brunnermeier and Cohen

2003; Jaffe and Palmer 1997; Lanjouw and Mody 1996). However, empirical evidence on the

effect of stringency of environmental policy on innovative behaviour remains limited, both with

respect to the overall effects of environmental policy on technological innovation, as well as the

more specific question of the extent to which this is reflected in patent activity. Nevertheless, there

is now increasing empirical evidence to support the contention that environmental policies do lead

to technological innovation. For recent reviews of the empirical literature on this theme see

Vollebergh (2007) and Jaffe, Newell and Stavins (2002).

This paper continues in the tradition of the latter approach and studies the effects of public

environmental policy (as proxied by PACE) and other factors on innovation in environmental

technologies, using patent data for an unbalanced panel of 16 countries for the period 1985-2004.

Unlike previous studies which used PACE at the sectoral level, this is the first econometric study

using PACE data at the cross-country level.4 The key hypothesis to be explored is the effect of

public environmental policy on innovation; and in particular, the possibly differential effect across

the alternative economic sectors undertaking PAC activities (i.e. public sector, private sector,

specialized producers). The role of government environmental R&D is also examined.

2. Data construction and interpretation

2.1. Patent counts as a measure of environment-related innovation

Patent data have been used as a measure of technological innovation because they focus on outputs

of the inventive process (Griliches 1990). This is in contrast to many other potential candidates

(e.g. research and development expenditures, number of scientific personnel, etc.) which are at best

imperfect indicators of the innovative performance of an economy since they focus on inputs.

4

Moreover, patent data provide a wealth of information on the nature of the invention and the

applicant, the data is readily available (if not always in a convenient format), discrete (and thus

easily subject to statistical analysis), and can be disaggregated to specific technological areas.

Significantly, there are very few examples of economically significant inventions which have not

been patented (Dernis and Guellec 2001).

However, patents are an imperfect measure of technological innovation for several reasons.

First, there is variation in the propensity for inventors to patent across countries and sectors. This is

due in part to the level of protection afforded by the patent, but also to the possibility of

appropriating rents from innovation by other means depending upon market conditions (e.g.,

industrial secrecy). In the empirical section of this paper, this concern over differences in the

propensity to patent is addressed by including a variable reflecting the overall patenting activity to

control for these effects across countries and over time.

Second, it is difficult to distinguish between the „value‟ of different patents on the basis of

patent applications. Most clearly, the use of unweighted patent counts would attribute the same

importance to patents for which there were no successful commercial applications with those which

are highly profitable. In this paper, this concern is addressed by using data on patent applications to

the European Patent Office (EPO), rather than individual patent offices.5 Through the EPO, the

applicant designates as many of the EPO member states for protection as it desires, rather than

applying to individual European patent offices among the 32 contributing countries. If the

application is successful, the patent is transferred to the individual national patent offices

designated for protection in the application. Given that EPO applications are more expensive than

applications to national patent offices, inventors typically first file a patent application in their

home country, and then apply to the EPO if they desire protection in multiple European countries

due to perceived market opportunities. As such, patent applications to the EPO are likely to be of

greater commercial value than the mean value of patent applications at national patent offices.

4 It is important to study these effects in a cross-country manner because large differences in per capita

emissions across countries exist (e.g., Australia‟s SOx emissions are almost 5-times higher than the OECD

average (OECD 2007a)).

5

While the use of EPO applications introduces a „quality‟ threshold to ensure that only

relatively valuable patents are included in the analysis, it introduces a potential source of bias.

While the European market is significant, it is still expected that there will be some bias toward

applications from European inventors (see Dernis and Guellec 2001). For a given invention, a

German inventor will be more likely to patent at the EPO than an American inventor. In the

empirical analysis undertaken in this study the bias associated with the use of EPO applications is

addressed through the inclusion of both country fixed effects and a control variable reflecting data

on total EPO applications by inventor country for all technology areas.

And finally, it can be difficult to identify relevant patent applications. Drawing upon

existing efforts to define „environmental‟ activity in sectoral terms, some previous studies have

related patent classes to industrial sectors using concordances (e.g., Jaffe and Palmer 1996). The

weaknesses of such approach are twofold. First, if the industry of origin of a patent differs from

industry of use of the patent, then it is not clear to which industrial sector a patent should be

attributed in the analysis. This is important when studying specifically “environmental” technology

because in this case the demand (users of technology) and supply (inventors of technology) of

environmental innovation may involve different entities. Often, “environmental” innovations

originate in industries which are not specifically environmental in their focus. For example,

technologies aimed at reducing wastewater effluents from the pulp & paper industry are often

invented by the manufacturing or chemicals industry (see e.g., Popp et al. 2007). On the other hand,

some “environmental” industries invent technologies which are widely applicable in non-

environmental sectors (e.g., processes for separation of packaging waste; separation of vapours and

gases).

More fundamentally, sectoral classifications are, by definition, based on commercial

outputs. As such there will be a bias toward the inclusion of patent applications from sectors that

produce environmental goods and services. The application-based nature of the patent

classification systems allows for a richer characterisation of relevant technologies. Consequently,

5 Using data on application, rather than granted patents, is more useful for international comparisons because

granting frequency varies across countries and over time (see e.g., Griliches 1990).

6

in this study patent classifications are used, rather than those of industrial or sectoral

classifications.6 Specifically, relevant patents were identified using the International Patent

Classification (IPC) system. However, IPC classes may be too broad for many areas of

“environmental” technology, leading to two possible types of error when searching for relevant

patents – inclusion of irrelevant patents and exclusion of relevant patents from the selected

classifications. Therefore keyword searches were used to filter only the relevant patents.

Patent data were extracted from the OECD Patent Database (OECD 2007b) using a search

algorithm based on a selection of IPC classes combined with keyword searches to target specific

areas of environment-related technology (Annex 1 gives the list of classes included; for the

complete search strategy see Schmoch 2003).7 The patent data are used to construct counts of

patent applications to the EPO in selected areas of environmental technology (air pollution, water

pollution, waste disposal, noise protection, and environmental monitoring), classified by inventor

country (country of residence of the inventor) and priority date (the earliest application date within

a given patent family). A panel of patent counts for a cross-section of all countries and over a time

period of 27 years (1978-2004) was obtained. Figure 1 shows the total number of EPO patent

applications by OECD countries in the five environmental domains. It shows that while water and

air pollution innovations have been increasing rapidly, the growth has been slower in the fields of

noise protection and environmental monitoring. Innovations related to waste disposal reached a

peak in 1991 and have declined since.

(Insert Figure 1 about here.)

Figure 2 gives patent counts in environmental technology for selected countries which have

exhibited significant levels of innovation. Germany has the highest number of patents, but relative

to the US and Japan, this partly reflects the „home bias‟ in EPO applications. France and the UK

6 While Jaffe and Palmer (1996) used patent totals (environmental and non-environmental patents) to study

the effect of environmental regulation on innovation, Lanjouw and Mody (1995) and Brunnermeier and

Cohen (2003) focus on environmental patents only, and their approach is thus similar to ours. However,

details on the selection of patent classes they used are not provided. 7 Following the discussion above, the search strategy includes not only „environmental‟ patent classes

covering end-of-pipe innovations, but also more general patent classes covering innovations related to

changes in production processes. In the absence of inclusion and exclusion keywords, the search algorithm

could overstate the former relatively to the latter.

7

both have at least 1000 patent applications over the period. These five countries represent between

74% and 84% of patent applications in each of the five domains. Germany alone, is responsible for

the highest number of filings in air, water, waste, and noise, while environmental monitoring is

dominated by the US and Japan.

(Insert Figure 2 about here.)

While Germany, Japan, the US, France and the UK are consistently important in

environmental technologies examined, other significant innovators in specific areas have included

Sweden (air), the Netherlands (water, monitoring), Italy (waste, noise) and Switzerland (noise)

(Table 1).

(Insert Table 1 about here.)

However, a comparison of the productivity of inventive activity across countries needs to

account for relative differences in the size of countries‟ scientific capacity.8 In Table 2, the counts

are weighted by country‟s gross domestic expenditure on R&D (GERD) to yield a measure of

patent intensity. On this basis, Germany as well as a number of smaller countries such as Austria,

Denmark, Switzerland, and Finland achieve the highest innovation output per dollar of R&D

expenditure.


2.2. Pollution abatement and control expenditures

Public policy may induce innovation by changing relative factor prices or introducing production

constraints. However, measurement of this effect is complicated because cross-country (or cross-

sectoral) data on regulatory stringency are rarely available or are not commensurable.

Consequently, various types of proxies have been used in the literature, including PACE measured

at the macroeconomic (e.g., Lanjouw and Mody 1996) or sectoral level (e.g., Brunnermeier and

Cohen 2003), the frequency of inspection visits (e.g., Jaffe and Palmer 1997), or various types of

derived measures (e.g., Johnstone et al. 2007).

8 For example, Madsen (2007) used the ratio of patents and real R&D expenditures as an indicator of

countries‟ research productivity.

8

The use of PACE data is very common in the empirical literature because it is one of the

few sources of quantitative information on environmental “compliance costs”. PACE includes

spending on PAC activities that are defined as “purposeful activities aimed directly at the

prevention, reduction and elimination of pollution or nuisances arising as a residual of production

processes or the consumption of goods and services” (OECD 2007c).9 This definition excludes

expenditure on natural resource management and risk prevention (such as prevention of natural

disasters and hazards), on nature protection (such as the protection of endangered species, the

establishment of natural parks and green belts), and on the exploitation and mobilisation of natural

resources (such as the supply of drinking water). Also excluded is expenditure that may primarily

satisfy health and safety requirements (such as expenditure intended for workplace protection) or

expenditure on the improvement of the production process for commercial or technical reasons,

even when they have environmental benefits (OECD 2007c).

However, PACE is only an imperfect measure of regulatory stringency. Several reasons

have been identified in the literature, including (a) the difficulty of identifying expenditures on

environmental compliance compared to what they would have been in the absence of

environmental regulations. The difficulty of establishing an appropriate baseline arises because

even in the absence of government regulation firms may still invest in such projects in order to

limit their potential exposure to liability and improve their environmental image with customers

(Jaffe et al. 1995); (b) Next, there is an important distinction between end-of-pipe solutions and

production process innovations, suggesting that it may be difficult for respondents to assign

expenditures to the latter. Specifically, firms may be unable to distinguish between the different

investment motives associated with adoption of integrated technologies. For example, what

proportion of expenditure on a new production process that increases material efficiency (and thus

reduces input costs) should be assigned to PAC? (see e.g., Lanjouw and Mody 1996); (c) Further,

firms could have an incentive to “strategically” overstate their PAC expenditures in order to

9 In this paper, consistent with this definition, the PACE data include only expenditure that is incurred

directly for PAC purposes (e.g., as a consequence of government environmental policies). Expenditure that

has positive environmental effects without being directly motivated by environmental concerns (e.g., energy

efficiency) is not included here. For the complete definition see Annex 2.

9

encourage regulators to weaken the degree of regulatory stringency, a common concern with

survey data; (d) Another concern associated with the use of aggregate measures of PACE to proxy

for stringency relates to cross-country differences in industrial composition. Countries with a lot of

polluting industry will have relatively high environmental compliance costs, regardless of the

stringency of their regulations (Levinson 1999); (e) Finally, despite significant efforts undertaken

to date, collection of PACE data is not fully harmonized across countries (OECD 2007c).

Despite these shortcomings, the PACE data is a rare source of information on the

opportunity costs created by countries‟ environmental policies and as such, if handled and

interpreted carefully, can be useful to study the effects of public environmental policies on

technological innovation. In particular, changes in opportunity costs due to increased regulatory

stringency, as proxied by higher PACE, are hypothesised to increase innovative behaviour targeted

at reducing environmental impacts of economic activity.

The PACE data used in this paper have been obtained from a series of annual surveys

published in OECD (2007c; 2003; 1996). The data are disaggregated into six environmental

domains -- including air, water, waste, land, noise, and monitoring (Table 3). In addition,

expenditures are disaggregated by the nature of the costs incurred, including (a) investment

expenditure, (b) internal current expenditure, and (c) transfer payments (such as subsidies and fees)

that are directly aimed at pollution abatement and control according to the abater principle (i.e.

sector where the PAC activity occurs) (OECD 2007c).10

Hence, PAC expenditure comprises actual

outlays and is thus conceptually different from PAC cost.


PACE is also disaggregated by the economic sector where the PAC activity occurs,

including the public sector, the business sector, and private and public specialised producers of

PAC services. Public PAC measures, which mainly concern waste and wastewater treatment, may

either be done directly by governments (central, regional, and local) and government agencies

10

Excluded are (a) calculated cost items (e.g. depreciation of fixed capital, cost of capital) as only actual

outlays are recorded, and (b) payments of interest, fines and penalties for non-compliance with environmental

regulations or compensations to third parties etc. as they are not directly linked with a PAC activity (OECD

2007c).

10

(further referred to as public sector) or be purchased as services from publicly-owned firms (further

referred to as public specialized producers). Private PAC measures, which mostly relate to

treatment or prevention of pollution to air and water and hazardous waste disposal from firm‟s own

operating activities, may either be done directly by the business sector or be purchased as services

from private specialized producers.11

Our dataset spans 30 countries for the period from 1985 to 2004. Three alternative PACE

variables are constructed representing PACE by the public sector including public specialized

producers (PACE_Public), PACE by the private sector (PACE_Private), and a dummy variable

(D_PrivateSP) with a unit value when data on private specialized producers is available and zero

otherwise.12

The PACE variables constructed and their interpretation are summarized in Table 4.


While there are a number of missing observations, Figures 3 and 4 provide time-series of

expenditures by the public and private sectors for selected countries in which the data is relatively

complete. In the case of public sector PACE Germany and Denmark appear to have relatively high

expenditures. For private sector PACE the two countries with the highest average percentages

(Czech Republic and Poland) have fallen recently.

(Insert Figures 3 and 4 about here.)

2.3. Other explanatory variables

In addition to regulatory stringency, which may induce innovation indirectly, governments often

encourage innovation directly through targeted R&D spending. Since PAC expenditures do not, by

definition, include expenditures on R&D, we use data on government budget appropriations and

outlays for R&D with the objective of control and care of the environment (GBAORD_Env). The

11

Specialized producers have grown in importance over the recent years as many of these activities have

increasingly been privatised or outsourced (e.g., municipal waste collection services, water and wastewater

treatment) (OECD 2007c). 12

Data on PACE by the public sector (PACE_Public) reported in OECD (2007c, 2003, 1996) include PACE

by public specialized producers. However, data on PACE by the business sector reported in OECD (2007c,

2003) do not, by construction, include PACE by private specialized producers (PACE_PrivateSP). This data

is available separately for some countries and some years. In order to avoid losing observations, and still be

able to isolate the “average” effect of private specialized producers, a new variable is constructed as a sum of

those two, PACE_Private = PACE_Business + PACE_PrivateSP, and a dummy variable (D_PrivateSP) is

created with a unit value when the data is available and zero otherwise. However, data on PACE by the

11

data are taken from the OECD Research and Development Statistics database (OECD 2007d) and

are normalized by GDP. The sign on this variable is expected to be positive.13

Aside from public policy, there are other important determinants of patenting activity for

environment-friendly technologies. Above all, the propensity of inventors from a particular country

to patent is likely to change over time, both because different strategies may be adopted to capture

the rents from innovation (e.g., Cohen et al. 2000) and because legal conditions may change

through time (e.g., Ginarte and Park 1997). In addition, inventors from non-European countries are

less likely to patent at the EPO (home country bias). For meaningful empirical analyses it is

therefore important to control statistically for these differences in the propensity to patent. As such

a variable was included reflecting total EPO patent applications (EPO_Total) filed across the

whole spectrum of technological areas (not only environmental). This variable thus serves both as a

„scale‟ and as a „trend‟ variable in that it controls for control for differences in the effects of the

size of an economy, its research capacity, etc. on innovation as well as changes in general

propensity to patent over time and across countries. The sign on this variable is expected to be

positive. Table 5 provides basic descriptive statistics for the dependent and explanatory variables.


3. Empirical model and results

An empirical model is developed in order to evaluate the effects of environmental policy and other

factors on patenting activity in selected areas of environmental technology. The following reduced-

form equation is specified:

tiititititi EPOGBAORDPACEEPATENTS ,,3,2,1, [1]

where i = 1,…,16 indexes country and t = 1985,…,2004 indexes year. The dependent variable is

measured by the number of patent applications in selected areas of environmental technology (air

pollution, water pollution, waste management, noise protection, and environmental monitoring).

private sector reported in OECD (1996) include also private specialized producers. Consequently, the dummy

variable equals unity for these observations.

12

The explanatory variables include a vector of proxies for regulatory stringency (PACEi,t),

government expenditures on environmental R&D (GBAORDi,t), and total EPO filings (EPOi,t).

Fixed effects ( i ) are introduced to capture unobservable country-specific heterogeneity. All the

residual variation is captured by the error term ( ,i t ). A negative binomial model is used to

estimate equation [1] (for details on count data models see e.g., Cameron and Trivedi 1998;

Maddala 1990; Hausman, Hall and Griliches 1984).

In the first model, a narrow definition of environmental technology is applied and a patent

count in technologies related to air pollution, water pollution and waste disposal is used as a

dependent variable. This is because these are the domains that are most affected by PAC

expenditures (OECD 2007c). Second, a broader definition of environmental technology is applied

and a patent count related to air pollution, water pollution, waste disposal, noise protection and

environmental monitoring is used as a dependent variable.

Alternative specifications are estimated for a pooled model and by including country fixed

effects. Applying a likelihood ratio test, we reject the null hypothesis that the fixed effects model

and the pooled model are equivalent. Hence, further discussion concerns only the results of the

fixed effects model. Table 6 (columns 1 and 2) gives estimated coefficients of the negative

binomial model using an unbalanced panel of 16 countries14

between 1985 and 2004.15

The

presence of missing observations and all-zero outcomes of patent count for some countries reduce

the size of the sample to 150 in the models estimated.


Differences in countries‟ scientific capacity and propensity to patent are mostly explained

by overall EPO patenting activity (EPO_Total), which is positive and statistically significant at the

1% level and higher in both models estimated.

13

Although these expenditures are also included in total R&D (GERD), the value of government expenditure

on environmental R&D is far too small to cause any problems of correlation. 14

Australia, Austria, Belgium, Canada, Finland, France, Germany, Italy, Japan, Korea, Netherlands,

Portugal, Slovakia, Sweden, United Kingdom, United States. 15

No PACE data is available for 1986.

13

Next we focus on variables which explain the direction of patenting. The estimated

coefficient of PACE by the private sector has a positive sign and is statistically significant at the

1% level and higher in both models estimated. The additional average effect of PACE by private

specialised producers is negative but insignificant. These results indicate that the cost-reduction

pressures in the private sector are effective in inducing inventive activity (and that the private

sector protects them through patenting).

The estimated coefficient of public sector PACE is insignificant in both models estimated.

The hypothesis that PACE by the public sector leads to increased patenting activity cannot be

confirmed. Several factors may be at play, including (a) lower inventive activity in the public

sector since cost increases (e.g., due to environmental compliance) do not provide the right signals

to innovate.16

This is well-known as public agencies are not profit maximizers and often face soft

budget constraints; (b) lower propensity to patent of public agencies because of their lesser concern

with rent appropriation (even if they do innovate, they do not patent). The importance of this effect

could be tested by including a variable which reflects the different propensity to patent for specific

technologies by the private and public sectors. Unfortunately this data is not available.

When it comes to government environmental R&D (GBAORD_Env), the estimated

coefficients have a positive sign and are statistically significant at the 5% level, suggesting that

government-financed research is a significant determinant of innovations in PAC activities.

Our results can be compared directly with those of previous studies. While Jaffe and

Palmer (1997) found that PACE had no impact on patenting activity (negative and insignificant

coefficient), Brunnermeier and Cohen (2003) found a positive and significant (5%) effect of PACE

on patenting. However, and as noted above, they used different definitions of „environmental‟

patents. Moreover, neither of these studies distinguished PACE for the public and private sectors.

And most importantly, their sample only included the U.S., with disaggregation across sectors.

Finally, an alternative measure of environmental policy stringency, based upon responses

to a survey of Chief Executive Officers undertaken by the World Economic Forum (WEF 2001,

16

However, innovation occurs if the signal is explicit – such as in the case of public funds being explicitly

devoted to environmental R&D (the coefficient on GBAORD is positive and significant).

14

through 2006), is used to complement the analysis. The results (columns 3 and 4 in Table 6)

broadly confirm the previous findings. Although the variable (WEF_STRNG) only represents the

average levels during 2001-2006, due to little variation in the index over time, the empirical

estimates provide a strong indication that more stringent environmental policies tilt the direction of

innovation towards more environment-friendly technologies.

4. Conclusions

This paper examines the impact of public environmental policy, as reflected in pollution abatement

and control expenditures, on innovations in environment-related technology. It is the first study to

look at these issues using a panel of countries. A strong relationship is found between patenting in

environmental technologies and general propensity to patent, government expenditures on

environmental R&D, and private (but not public) PACE expenditures. This suggests that the

stringency of environmental policy may be an effective means of inducing innovation if it is

translated in PAC expenditures by the private sector. In the public sector, expenditures on PAC

activities do not have a significant effect on environmental patenting and, if technological

innovation is the goal, public resources should rather be spent directly on R&D. These results are

broadly confirmed with a subsequent analysis on a broader cross-section of countries, using an

alternative measure of environmental policy stringency.

One of the important limitations of this research is the relatively small sample size. The

primary constraint on increasing sample size arises from missing observations with respect to the

PACE variable. Moreover, the use of PACE data as a proxy for regulatory pressure is not entirely

satisfactory. In an attempt to address these limitations, an alternative measure of regulatory

stringency at the aggregate level, which is commensurable across countries, is used in this paper.

In order to overcome the shortcomings in this paper and previous research, further work in

this area might include the development and analysis of a panel dataset for a sub-sample of

countries in which regulatory stringency for a particular pollutant is commensurable across

countries. This might be feasible for pollutants where performance standards with similar points of

incidence are commonly applied.

15

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18

Table 1. Number of EPO patent applications (1978-2004 annual average)

Air Water Waste Noise Monitoring AWW ALL sum

Australia 2.23 6.08 5.03 3.41 3.10 20.59 25.02 297

Austria 5.43 8.41 6.68 6.23 2.48 35.49 43.56 525

Belgium 2.56 6.27 4.45 4.10 5.59 21.41 30.34 360

Canada 3.81 9.23 4.49 5.85 3.43 30.85 39.51 466

Czech Republic 1.29 1.67 1.64 1.33 0.67 3.29 3.39 22

Denmark 3.69 4.87 4.91 5.98 1.88 20.28 25.43 309

Finland 3.23 4.55 3.99 3.16 4.88 17.76 25.56 297

France 16.59 28.30 30.33 24.06 24.88 126.25 183.60 2225

Germany 92.00 86.17 81.37 73.50 38.39 448.51 581.10 7000

Greece 1.03 1.35 1.13 1.33 0.83 3.47 3.60 31

Hungary 1.07 1.93 2.27 1.33 0.70 4.67 5.15 52

Iceland 0.00 0.38 0.00 0.00 0.00 0.83 0.83 1

Ireland 0.84 1.80 1.00 1.22 1.25 3.48 4.19 34

Italy 7.69 9.91 12.18 10.19 5.33 49.80 65.16 769

Japan 69.87 39.62 42.45 33.58 44.06 283.88 378.73 4429

Korea 2.08 4.51 4.02 3.25 1.58 13.03 15.57 125

Luxembourg 1.33 0.67 0.50 1.33 1.00 2.22 2.74 18

Mexico 0.00 1.00 1.00 0.00 0.00 2.00 2.00 3

Netherlands 3.97 11.02 7.21 6.81 7.52 37.65 54.02 662

New Zealand 0.96 1.05 0.80 1.67 0.73 1.83 1.89 16

Norway 1.30 3.14 2.11 1.88 1.81 8.42 10.02 120

Poland 0.88 1.49 2.40 1.33 0.80 3.77 4.26 29

Portugal 1.00 1.05 1.00 1.50 1.00 1.91 2.13 12

Slovakia 0.00 0.90 1.00 1.00 0.00 1.63 1.85 8

Spain 1.35 3.34 2.74 4.29 2.17 9.22 11.66 130

Sweden 8.02 9.70 8.15 7.45 6.23 44.88 58.67 715

Switzerland 6.70 9.37 9.23 8.89 5.29 41.28 56.16 681

Turkey 1.00 1.00 0.00 2.00 0.00 2.00 2.50 6

UK 13.56 22.41 13.54 10.35 14.45 90.59 119.77 1453

US 52.21 80.12 51.85 49.58 72.13 332.12 474.80 5707

OECD Total 292.50 347.49 286.17 359.95 336.42 1642.60 2212.95 26504

Note: AWW = Air + Water + Waste; ALL = Air + Water + Waste + Noise + Monitoring

Care has been taken to avoid double-counting of patents which fall in multiple categories.

19

Table 2. Number of EPO patent applications per dollar of R&D expenditure (Gross Domestic

Expenditures on R&D, in billions of US dollars, using PPP and 2000 prices)

Air Water Waste Noise Monitoring AWW ALL

Australia 0.38 1.02 0.85 0.57 0.52 3.46 4.21

Austria 1.78 2.76 2.19 2.05 0.81 11.65 14.31

Belgium 0.62 1.52 1.08 0.99 1.35 5.19 7.35

Canada 0.32 0.79 0.38 0.50 0.29 2.63 3.37

Czech Republic 0.73 0.95 0.94 0.76 0.38 1.88 1.94

Denmark 1.64 2.16 2.18 2.65 0.83 8.98 11.27

Finland 1.19 1.67 1.47 1.16 1.80 6.53 9.39

France 0.57 0.97 1.04 0.82 0.85 4.32 6.28

Germany 2.19 2.05 1.94 1.75 0.91 10.69 13.84

Greece 1.34 1.76 1.47 1.74 1.09 4.53 4.70

Hungary 1.39 2.51 2.95 1.73 0.91 6.07 6.69

Iceland 0.00 3.39 0.00 0.00 0.00 7.52 7.52

Ireland 1.11 2.37 1.32 1.61 1.65 4.58 5.52

Italy 0.56 0.72 0.89 0.74 0.39 3.64 4.76

Japan 0.85 0.48 0.52 0.41 0.54 3.47 4.63

Korea 0.13 0.27 0.24 0.20 0.10 0.79 0.94

Luxembourg 3.39 1.71 1.27 3.39 2.54 5.65 6.97

Mexico 0.00 0.33 0.33 0.00 0.00 0.65 0.65

Netherlands 0.58 1.61 1.05 0.99 1.10 5.49 7.88

New Zealand 1.33 1.46 1.11 2.31 1.01 2.54 2.62

Norway 0.68 1.64 1.10 0.98 0.94 4.40 5.23

Poland 0.38 0.64 1.03 0.57 0.34 1.62 1.84

Portugal 1.16 1.22 1.16 1.74 1.16 2.22 2.47

Slovakia 0.00 1.80 1.99 1.99 0.00 3.25 3.69

Spain 0.25 0.62 0.51 0.80 0.40 1.71 2.16

Sweden 1.19 1.44 1.21 1.11 0.93 6.69 8.74

Switzerland 1.35 1.89 1.86 1.79 1.07 8.32 11.32

Turkey 0.45 0.45 0.00 0.90 0.00 0.90 1.12

UK 0.54 0.89 0.54 0.41 0.57 3.58 4.74

US 0.26 0.40 0.26 0.25 0.36 1.65 2.36

Note: AWW = Air + Water + Waste; ALL = Air + Water + Waste + Noise + Monitoring

Care has been taken to avoid double-counting of patents which fall in multiple categories.

20

Table 3. Environmental domains related to PAC activities

En

vir

on

men

tal

mgm

t

En

vir

on

men

tal

pro

tect

ion

Po

lluti

on

abat

emen

t an

d

con

tro

l (P

AC

)

1. Protection of ambient air and climate

2. Wastewater management

3. Waste management

4. Protection and remediation of soil,

groundwater and surface water

5. Noise and vibration abatement

6. Protection against radiation

7. Protection of biodiversity and landscape

8. Research & Development

9. Other environmental protection activities

Nat

ura

l

reso

urc

e

mgm

t

Source: Adapted from OECD (2007: 9-18). For further details see CEPA (2000).

Table 4. PACE variables and their interpretation

Coefficient on variable Interpretation

PACEPublic

Effect of PACE by the public sector (incl. public SP)

PACEPrivate

Effect of PACE by the private sector (incl. private SP)

PACEPrivate

* DPrivateSP

Additional average effect of PACE by private specialized

producers, for the subsample of countries where such data

is available.

Table 5. Descriptive statistics for the sample of 16 countries

Variable Unit Obs Mean Std. dev. Min Max

PATENTS_AWW count 648 31.28 60.98 0 287

PATENTS_ALL count 648 40.50 78.37 0 375

PACE_Public % GDP 302 0.60 0.38 0.10 4.00

PACE_Private % GDP 206 0.59 0.37 0.00 2.50

D_PrivateSP binary 206 0.05 0.21 0 1

GBAORD_env_n % GDP 417 0.0153 0.0095 0.0004 0.0471

EPO_Total count (thousands) 948 1.7105 4.3878 0.0002 30.9420

Note: PATENTS_AWW includes counts for air pollution, water pollution, and waste disposal

PATENTS_ALL includes counts for air pollution, water pollution, waste disposal, noise

protection, and environmental monitoring.

21

Table 6. Regression estimates of NB models with country fixed effects

Dependent variable: Air pollution;

Water pollution;

Waste disposal

Air pollution,

Water pollution,

Waste disposal,

Noise protection;

Environmental

monitoring

Air pollution;

Water pollution;

Waste disposal

Air pollution,

Water pollution,

Waste disposal,

Noise protection;

Environmental

monitoring

(1) (2) (3) (4)

PACE_Public -0.058 0.011

(0.123) (0.111)

PACE_Private 0.364***

0.325***

(0.112) (0.100)

PACE_Private -0.100 -0.046

× D_PrivateSP (0.069) (0.062)

WEF_STRNG_avg

0.648***

0.601***

(0.129) (0.124)

GBAORD_env_n 10.025**

8.187**

20.824***

19.662***

(4.377) (3.940) (3.127) (3.059)

EPO_totals 0.018***

0.023***

0.023***

0.026***

(0.003) (0.003) (0.002) (0.002)

Intercept 3.096***

3.188***

-2.597***

-2.329***

(0.243) (0.241) (0.743) (0.714)

Observations 150 150 626 626

Groups 16 16 33 33

Log-likelihood -471.47 -497.91 -1821.38 -1946.26

Wald chi2 63.90 116.47 235.46 290.93

(Prob > chi2) (0.000) (0.000) (0.000) (0.000)

Notes:

*,

** and

*** refer to 10%, 5% and 1% level of statistical significance. Standard errors are in

parentheses. The dependent variable is the count of patent applications in a given technological area. When

fixed effects are included, the intercept represents the average value of the country-specific fixed effects.

22

Figure 1. Number of EPO Patent Applications in Selected Areas of Environmental

Technology

Figure 2. Number of EPO Patent Applications in Environmental Technology, by Inventor

Country

23

Figure 3. PACE expenditures by the public sector (incl. public SP) in selected countries

Figure 4. PACE expenditures by the business sector and private specialised producers in

selected countries

24

Annex 1. Patent classes and keywords for selected areas of environmental technology

AIR POLLUTION IPC class Keywords

Separating dispersed particles from gases or vapour , e.g. air, by

electrostatic effect B03C 3/00

(exhaust, effluent,

flue, combustion,

waste) AND (gas,

gases, smoke, air)

Processes for making harmful chemical substances harmless, or less

harmful, by effecting a chemical change in the substances A62D 3/00

Separating dispersed particles from gases or vapours by gravity, inertia,

or centrifugal forces B01D 45/00

Filters or filtering processes specially modified for separating dispersed

particles from gases or vapours B01D 46/00

Separating dispersed particles from gases, air or vapours by liquid as

separating agent B01D 47/00

Separating dispersed particles from gases, air or vapours by other

methods B01D 49/00

Combinations of devices for separating particles from gases or vapours B01D 50/00

Auxiliary pre-treatment of gases or vapours to be cleaned B01D 51/00

Chemical or biological purification of waste gases, e.g. engine exhaust

gases, smoke, fumes, flue gases, aerosols B01D 53/00

Chemical or biological purification of waste gases B01D 53/34-36

Dust extraction equipment on grinding or polishing machines B24B 55/06-10

Details of, or accessories for, apparatus for shaping the material;

Exhausting or laying dust B28B 17/04

Accessories specially adapted for for removing or laying dust, e.g. by

spraying liquids; for cooling work B28D 7/02

Details of, or accessories for, portable power-driven percussive tools;

Removing or laying dust by liquid or by exhausting dust-loaded air B25D 17/14-18

Auxiliary measures taken, or devices used, in connection with loading

or unloading; Preventing escape of dust B65G 69/18

Materials not provided for elsewhere; for dust-laying or dust-

absorbing C09K 3/22

Use of additives to fuels or fires for particular purposes for reducing

smoke development C10L 10/02

Arrangements for confining or removing dust, fly, or the like D01H 11/00

Blast furnaces; Dust arresters C21B 7/22

Manufacture of steel; Removal of waste gases or dust; Offtakes or

separating apparatus for converter waste gases or dust C21C 5/38-40

Means or methods for preventing, binding, depositing, or removing

dust; Preventing explosions or fires E21F 5/00

Exhaust or silencing apparatus for rendering innocuous by thermal or

catalytic conversion of noxious components of exhaust F01N 3/08-38

Apparatus for treating combustion-air, fuel, or fuel-air mixture, by

catalysts F02M 27/02

Combustion apparatus with arrangements for burning uncombusted

material from primary combustion F23B 5/00

Combustion apparatus characterised by arrangements for returning

combustion products or flue gases to the combustion chamber for

completing combustion

F23C 9/06

Shaft or like vertical or substantially vertical furnaces; Arrangements of

dust collectors F27B 1/18

Electrical control of exhaust gas treating apparatus F01N 9/00

25

WATER POLLUTION IPC class Keywords

Accommodation for crew or passengers; Soil-water discharges B63B 29/16

Barges or lighters for collecting pollution from open water B63B 35/32

Arrangements of installations for treating waste-water or sewage B63J 4/00

Materials for treating liquid pollutants, e.g. oil, gasoline, fat C09K 3/32

Treatment of water, waste water, or sewage C02F 1/00

Biological treatment of water, waste water, or sewage C02F 3/00

Aeration of stretches of water C02F 7/00

Multistep treatment of water, waste water or sewage C02F 9/00

Devices for treatment of sludge C02F 11/00

Apparatus for cleaning or keeping clear the surface of open water E02B 15/00

(NOT 15/02)

Methods or installations for obtaining or collecting drinking water or

tap water E03B 3/00

WASTE DISPOSAL IPC class Keywords

Processes for making harmful chemical substances harmless, or less

harmful, by effecting a chemical change in the substances A62D 3/00

( exhaust, effluent,

flue, combustion,

waste) AND (gas,

gases, smoke, air)

Treatment of water, waste water, sewage, or sludge

C02F

(exhaust, effluent,

flue, combustion)

AND (gas, gases,

smoke, air) Chemical or biological purification of waste gases

B01D 53/34-

36

Disposal of solid waste B09B

Cremation furnaces; Consuming waste by combustion F23G

Treating radioactively contaminated material; Decontamination

arrangements therefor G21F 9/00

NOISE PROTECTION IPC class Keywords

Details of, or accessories for, portable power-driven percussive tools;

Arrangements of noise damping means of exhaust silencers B25D 17/11-12

Arrangements for absorbing or reflecting air transmitted noise from

road or railway traffic E01F 8/00

Sanitary or other accessories for lavatories; Noise-reducing means

combined with flushing valves E03D 9/14

Constructions and structures; Noise or sound insulation, absorption, or

reflection E04B 1/82-90

Flooring; Separately-laid insulating layers; Other additional insulating

measures; Floating floors for sound insulation E04F 15/20

Doors, windows, or like closures for special purposes; Border

constructions for insulation against noise E06B 5/20

Silencing apparatus characterised by method of silencing F01N 1/00

Exhaust or silencing apparatus, or parts thereof having two or more

separate silencers in series or in parallel F01N 7/02-04

Silencers specially adapted for steam engines F01B 31/16

Acoustic insulation F02B 77/13

Air intakes for gas-turbine plants or jet-propulsion plants having

provisions for noise suppression F02C 7/045

Intake silencers, combined air cleaners and silencers specially adapted

for, or arranged on, internal-combustion F02M 35/12-14

Devices or appurtenances for use in, or in connection with, pipes or

pipe systems; Noise absorbers F16L 55/033

26

Silencing means for blasting operations F42D 5/055

Methods or devices for protecting against, or damping of, acoustic

waves, e.g. sound G10K 11/16

Insulating elements for vehicles, e.g. for sound insulation B60R 13/08

sound, noise

Ground or aircraft-carrier-deck installations for reducing engine or jet

noise; Protecting airports from jet erosion B64F 1/26

Protection of permanent way against development of dust or against the

effect of wind, sun, frost, or corrosion; Means to reduce development of

noise

E01B 19/00

Design or layout of roads, e.g. for noise abatement, for gas absorption E01C 1/00

Plants characterised by the form or arrangement of the jet pipe or

nozzle; F02K 1/

.. using fluid jets to influence the jet flow for attenuating noise .. 1/34

.. nozzles having means, e.g. a shield, reducing sound radiation in a

specified direction .. 1/44

.. nozzles having means for adding air to the jet or for augmenting the

mixing region between the jet and the ambient air, e.g. for silencing .. 1/46

Detonation-wave absorbing or damping means; Blasting mats F42D 5/05

Filtering, cooling, or silencing cooling-air F01P 11/12

Air intakes for gas-turbine plants or jet-propulsion plants F02C 7/04

Heat or noise insulation F02C 7/24

Means in valves for absorbing fluid energy for preventing water-

hammer or noise F16K 47/02

Devices or appurtenances for use in, or in connection with, pipes or

pipe systems; Energy absorbers; Noise absorbers F16L 55/02

NOT (F41,

G01, H01, H02,

H03, H04, H05)

(absorb, reduc,

abate, barrier,

prevent, deaden,

dampen, anti) AND

(sound, noise)

NOT (F01N) silencer

ENVIRONMENTAL MONITORING IPC class Keywords

Investigating or analysing materials by determining their chemical

or physical properties

G01N

((toxi, pollu, contaminat,

monitor) AND (water,

air, atmos, soil))

OR

((water, air, atmos, soil)

AND (effluent, flue,

exhaust, water))

OR

(environment AND

(water, air, atmos, soil))

OR

((water, air, atmos, soil)

AND (analys, measur))

Measurement of mechanical vibrations or ultrasonic, sonic, or

infrasonic waves

G01H

(NOT 1/00) noise

Investigating or analysing materials by specific methods: water G01N 33/18

Investigating or analysing materials by specific methods: Earth

materials G01N 33/24

Measuring X-radiation, gamma radiation, corpuscular radiation, or

cosmic radiation

G01T 1/00

(NOT 1/29-40)

Details of radiation-measuring instruments G01T 7/00

Note: Keyword searches were applied on titles of patent documents. All keywords were used with a wildcard.

27

Annex 2. Environmental domains related to PAC activities

1 Protection of ambient air and climate

1.1 Prevention of pollution through in-process modifications -- for the protection of ambient air;

for the protection of climate and ozone layer

1.2 Treatment of exhaust gases and ventilation air -- for the protection of ambient air; for the

protection of climate and ozone layer

1.3 Measurement, control, laboratories and the like

1.4 Other activities

2 Wastewater management

2.1 Prevention of pollution through in-process modifications

2.2 Sewerage networks

2.3 Wastewater treatment

2.4 Treatment of cooling water



3 Waste management

3.1 Prevention of pollution through in-process modifications

3.2 Collection and transport

3.3 Treatment and disposal of hazardous waste -- thermal treatment; landfill; other

3.4 Treatment and disposal of non-hazardous waste -- incineration; landfill; other



4 Protection and remediation of soil, groundwater and surface water

4.1 Prevention of pollutant infiltration

4.2 Cleaning up of soil and water bodies

4.3 Protection of soil from erosion and other physical degradation

4.4 Prevention and remediation of soil salinity



5 Noise and vibration abatement (excluding workplace protection)

5.1 Preventive in-process modifications at the source -- road and rail traffic; air traffic; industrial

and other noise

5.2 Construction of anti noise/vibration facilities -- Road and rail traffic; Air traffic; Industrial and

other noise



6 Protection against radiation (excluding external safety)

6.1 Protection of ambient media

6.2 Transport and treatment of high level radioactive waste



Source: Adapted from OECD (2007: 17-18). For further details see CEPA (2000).

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