j_2004, moenius, information versus product adaptation - the role of standards in trade

Electronic copy of this paper is available at: http://ssrn.com/abstract=608022

Information versus Product Adaptation:

The Role of Standards in Trade

Johannes Moenius Kellogg School of Management

Northwestern University

February 2004

ABSTRACT This paper examines the commonly held view that country-specific product and

process standards are barriers to trade and that harmonizing standards promotes inter-national trade. The econometric analysis generally confirms that bilaterally shared stan-dards are favorable to trade. However, it does not find that the number of country-spe-cific standards of importers is a barrier to trade on average. While country-specific standards of importers reduce imports for non-manufactured goods (e.g. agriculture), they do promote trade in the manufacturing sector. Information costs appear to be an explanation for this puzzle: if goods have to be adapted to a foreign market, then coun-try-specific standards of the importing country offer valuable information for adapting the product to that market. Otherwise, this information would be costly to gather.

Evanston, IL, 60208-2013, [email protected]. The author is

indebted to Jim Rauch and David Riker for numerous discussions. Helpful comments were provided by John Conlisk, Clive Granger, Gordon Hanson and David Hummels. The author would also like to thank Ulrich Blum, Gisela Eickhoff, Isabelle Junginger and Armin Tpfer from the DIN-Research Center at the Technical University of Dresden, Germany, whose financial support is gratefully acknowledged.

Electronic copy of this paper is available at: http://ssrn.com/abstract=608022

1. INTRODUCTION

The common perception of economists and politicians alike is that country-

specific standards are barriers to trade. Consequently, internationally shared standards

should be trade-promoting. Examining a simple example, the intuition is clear: since

the US operates on the 110 Volts standard and Germany operates on a 220 Volts basis,

every coffee-maker exported from Germany to the US either has to be modified in

production or the end user has to buy additional adapters and transformers. In both

cases, there are costly modifications or additions. These could be avoided if those two

countries operated on the same voltage-standard.

The European Union spends enormous efforts in coordinating standards across

Europe in an effort to promote trade among its member nations. In 1975, there were 20

harmonized standards in Europe. In 1999, there were nearly 5,500. More than 270

Committees work on different projects within the European Standardization Institute

(CEN) alone. Nearly 40 percent of their funds come directly from the European Union.

The CEN has 20 national member institutes that actively contribute to work at CEN as

well as implement European Standards in their national economies.1

The International Organization for Standardizations (ISO) main effort is to

harmonize standards around the globe. The ISO alone spends close to $100 million on

these efforts each year. 133 national standardization bodies participate in nearly 3,000

technical work-groups and committees. Approximately 12,000 international standards

are printed on a total number of 320,000 pages of information.2 The motivation for all

these efforts is to promote trade, yet little is known about the magnitude of the effect of

1 CEN (1999)

2 ISO (1999)

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standards on trade. The theoretical literature is inconclusive, and the few empirical

studies suffer from serious data problems.

This paper attempts to fill this gap. It uses a newly constructed panel data set

with data on country-specific and bilaterally shared standards for 471 industries in 12

countries during the time-period 1980-1995. We estimate a gravity relationship that

includes measures of shared and country-specific product and process standards. The

results confirm the general view that shared standards promote trade. On the other

hand, country-specific standards of importers are expected to reduce trade volumes. If

product adaptation is costly and exporters have to adjust their goods to the foreign

market due to differing country-specific standards, then these differing country-specific

standards should impede trade flows. Surprisingly though, we find that country-specific

(non-shared) standards of importers are also trade promoting on average. However,

regressions on an industry level reveal that this is not generally the case. In non-

manufacturing industries like agriculture, a large number of country-specific standards

in the importing country indeed hampers trade as predicted. But in manufacturing, a

positive effect of the number of country-specific standards of importers dominates.

The existing literature does not provide satisfactory answers to that puzzle.

Therefore an alternative explanation is proposed. Standards, whether country-specific

or shared, reduce information costs and allow for easier contracting.3 Country-specific

standards may at the same time increase adaptation costs. But if goods have to be

adapted to foreign markets, for example if consumer tastes or production technologies

vary across countries, then exporters are assisted by a large number of informative

3 This conjecture is supported by a survey of the German DIN-Institute: 40 % of all respondents indicate that standards allow for easier contracting both nationally and internationally. See Bahke (1999)

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standards that describe the export market.4 In non-manufacturing industries, products

are generally homogeneous, so informational requirements are low, and product-

adaptation costs likely dominate information costs.5 In manufacturing industries,

however, informational requirements are relatively high. Since standards lower

information gathering costs, the benefits of this cost reduction tend to outweigh the

additional adaptation costs, which may be increased by the same standards. Additional

empirical evidence is supportive of this claim.

The paper proceeds as follows: section two clarifies the basic concepts and

reviews the theoretical literature. Section three describes the estimation procedure,

section four the data set. Section five presents the empirical evidence. Section six

outlines the transaction-cost argument and contrasts the findings in this paper to the

existing empirical literature. Section seven concludes.

2. THEORETICAL FRAMEWORK

In this section, types of standards are identified and the relevant characteristics

are introduced. The measurement of shared standards is then described. The discussion

of previous research follows, and the theoretical predictions of the different branches of

literature are summarized in a table at the end of this section.

4 See Swann et al. (1996) for a related argument.

5 For example, institutional standards in agriculture are mostly concerned with testing procedures ensuring certain quality aspects of agricultural products. There are standards to determinate the content of sodium of vegetable-containing food for babies and infants, to determine the bulk density of fertilizers, and to determine the diameter of cigarettes. If exporters use differing testing procedures and quality levels in their own countries (or non at all), then they will likely produce varieties that need costly modification before they are acceptable in the export market. Testing or quality requirements need not be government enforced: large buyer associations in the export market can also insist on application of standards, thereby reducing competition from potential importers for local producers.

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2.1 What Are Standards?

Standards as used in this paper are product and process specifications intended

to harmonize the treatment of intermediates in the production process or the attributes

of final goods. The objectives of standards are to raise the quality of output, to protect

workers, consumers or the environment from potential hazards, or to ensure

compatibility among products or intermediates. Three types of standards can be

distinguished in terms of their origin. If standards evolve out of the market process,

they are generally referred to as de facto standards. Standards imposed by law are

called de jure standards. The largest number of standards, however, results from

coordination in committees and standardization institutions like the International

Organization for Standardization (ISO), the American National Standardization Institute

(ANSI) and the German DIN-Institute. These are generally referred to as institutional

standards.6 This study focuses on institutional standards. In contrast to de jure

standards, the adoption of institutional standards is voluntary. In contrast to de facto

standards, institutional standards are well-documented.

The measure of standards used in this study is the number of documents that

specify the details of standards for a particular industry, country, and year. In general,

we count one document as one standard. However, the methods for documenting

institutional standards vary across countries. For example, let us assume the technical

details about TV-tubes are outlined in one document in Germany, and therefore we

count them as one standard. In Spain, the exact same information is spread over three

documents, which we count as three standards. Although identical in terms of

6 There is some overlap between de jure and institutional standards, since the legislator sometimes changes institutional standards into de jure standards.

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informational content, our measure indicates that Spain has three times as many

standards as Germany for TV-tubes.7 With this caveat in mind, the number of total

standards in a country is just the number of documents counted for a particular industry

and year. The measure of country-specific standards, which is used in the estimation

below, corrects for bilaterally shared documents. For example, take the case where

Germany has 50 standards for processed foods, but it shares 20 of them with France.

Therefore the measure for country specific standards of Germany relative to France is

30. If it shares 40 of them with Belgium, then the measure of country-specific standards

in that industry for Germany relative to Belgium is 10.

For shared standards, the estimation procedure does not offer a simple remedy.

Therefore it is necessary to be aware of what we count as a shared standard. If

Germany has one document that describes a certain standard and Spain has three

documents that describe the same standard, then this is counted as three links between

those two countries in a particular industry and year. Therefore, the unit of

measurement for shared standards is links between documents, since measures of the

informational content of each document are not readily available. For ease of

exposition, the number of links will be called the number of shared standards

throughout the paper.

The economic analysis below will not distinguish between health, safety and

environmental requirements on the one side and standards to ensure product quality and

compatibility on the other. One reason is that the numbers of health and environmental

7 In regression analysis, the coefficient on the Spanish standard-counts does not need to be evaluated differently than the coefficient on German Standard counts. This is due to our logarithmic specification, where factors that just enter multiplicatively are absorbed in fixed effects. This assumes that Spain consistently packages the same amount of information in three times as many documents as Germany.

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standards in our database is very small.8 Moreover, institutional standards, which form

the basis of our analysis, are voluntarily adopted by firms. Economic reasoning

suggests that firms will only adopt measures if they benefit from doing so. Therefore, if

firms apply environmental standards voluntarily, they must benefit from it. They also

apply product standards when they gain from increased compatibility with other

products or if adoption of the standard signals that the product is of higher quality. In

this respect, health and environmental standards do not differ from quality and

compatibility standards as long as both are voluntarily used. Finally, even if

environmental standards have qualitatively opposite effects on the flow of trade, they

will only partially offset the effect of quality and compatibility standards, and the result

will be a bias in the estimated impact of standards on trade towards zero. Therefore,

any estimation that counts only quality and compatibility standards should find even

more significant effects of standards on the flow of international trade.

2.2 Previous Research

There are two major findings about the existing theoretical literature: first, only

a very small part of the economics literature on standardization is concerned with trade

issues.9,10 Therefore, one has to additionally rely on the literature on non-tariff

8 See table 2 in the Appendix A. The ISO lists 440 environmental standards out of a total of nearly 12,000 Standards. In our database, the number of health- and environmental standards seems to be considerably smaller.

9 For excellent surveys of the literature on standardization, see e.g. Farrell and Saloner (1987), David and Greenstein (1990), Katz and Shapiro (1994) and Matutes and Regibeau (1996).

10 Some exceptions are Matutes and Regibeau (1996), Kende (1991), Gandal and Shy (1996), Wallner (1998) and Jeanneret and Verdier (1996). Matutes and Regibeau (1996) arrive at the same evaluation.

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barriers to trade, non-price competitiveness and economic integration as a framework

for analyzing the effect of harmonizing standards.11 Second, the predictions of the

various branches of this literature span the entire set of possible outcomes. For each

type of standard (country-specific standards of importers and exporters as well as

shared standards), there is at least one theory that predicts a positive effect and another

one that predicts a negative effect. The net effect, from a theoretical point of view, is

ambiguous.

For ease of exposition, the literature is first reviewed along the dimensions

spanned by these branches and then compared in table 1. Key terms referred to in the

table are printed in italics in the text. In section six of this paper, the predictions of the

theories are weighed against the results of the econometric exercises.

First, the literature directly concerned with standards in an international context

is very closely related to the literature on non-tariff barriers. It is mostly concerned with

incentives to comply with, lobby for or enforce standards (Barrett and Young 2001,

Fischer and Serra 2000), taking the non-tariff barrier effect of standards as given.12 We

therefore examine it together with what we call the mainstream literature on non-tariff

barriers to trade. In this literature, the predominant view is that country-specific

standards of importing countries are a typical example of non-tariff barriers to trade

(NTB) (Harrigan 1993, Casella 1997). While the literature on NTBs is huge13, their

empirical relevance seems to be small (Harrigan 1993). This may partly be a

11 While non-price competition is a textbook topic, not much work seems to have been devoted to that in a trade context. Exceptions include Aiginger (1997) and Chao and Patokiprapha (1997).

12 For a detailed descriptive account, see Sykes (1995)

13 See Stern (1973) for an early review of the literature and Deardorff and Stern (1998) for a more recent treatment.

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measurement problem (Laird and Yeats 1990). Since coverage ratios (the percentage of

goods in an industry that are subjected to NTBs) are surprisingly high (Nogues et al

1986, Harrigan 1993), the measured effect is even more surprisingly low. More recent

research confirms the view that NTBs may have a smaller influence than economists

previously assumed (Hummels 1999). Nevertheless this branch of the literature

predicts a negative effect of country-specific standards of importers on imports.

Consequently, shared standards should have a positive effect on imports. There is no

prediction for the effect of country-specific standards of exporters.

Some extensions include that low-tech countries have trouble meeting high-tech

standards and that large countries have an incentive to form strategic alliances to

exclude smaller countries (Gandal and Shy 2001, Wallner 1998). As before, this

predicts a negative effect of country-specific standards of importers and a positive

effect of shared standards.

A version of the "competitive disadvantage" argument (Swann et al. 1996)

claims that a large number of country-specific process standards raises the costs of local

firms14 and therefore lowers their cost competitiveness. This in turn should promote

imports and reduce the exports of these highly regulated local firms. On the other hand,

the argument does not provide a prediction for the aggregate effect of shared standards

on the volume of trade.

Another version of this argument focuses on country-specific product standards

instead: in industries were there are large buyers who demand tailored products defined

by a large number of standards, local producers will have a barrier to overcome should

they wish to export these specialized products. They are in a standardization-trap.

14 This is confirmed by the survey mentioned above. See footnote 3.

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Grupp and Schnring (1990, 1991) find evidence that supports this argument in the pre-

deregulation French and Japanese telecommunications industry. This theory predicts a

negative effect of country-specific standards on both imports and exports, but a positive

effect of shared standards.

An alternative branch of the literature is based on a signaling argument:

standards increase the perception of product quality (Jones and Hudson 1996) and this

increased perception of product-quality improves the competitive advantage of firms

applying them (e.g., Jeanneret and Verdier 1996).15 In the oligopoly frameworks used

for the analysis, a larger number of standards promotes exports. There is no clear

prediction for the shared standards or country-specific standards of importers.

Finally, standardization may reduce the number of varieties available to

consumers (Farell and Saloner 1986). Although this must be balanced against scale

economies, this loss of variety may actually reduce trade.16 The effect of reduced

differentiation may outweigh the effect of reduced barriers.

Table 1 summarizes the predictions. According to table 1, shared standards

should most likely be trade-promoting, country-specific standards of importers are

likely to be import-reducing, and the effect of country-specific standards of exporters is

indeterminate. Clearly, standards have many counterbalancing effects on the pattern of

trade. Some are more dominant in particular industries. In the empirical analysis

15 See Swann et al. (1996) for an argument that is grounded in the management literature.

16 Matutes and Regibeau (1988) note that standardization may increase the variety available to consumers in the case of what they call mix-and-match goods. Shared standards consequently lead to more trade in this case. This is observationally equivalent to the first branch of the literature and will therefore not be treated separately.

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below, we investigate these hypotheses, while allowing for separate stories in clearly

dissimilar industries.

3. EMPIRICAL SPECIFICATIONS

One of the most successful and therefore widely used frameworks for empirical

analysis of trade-flows between countries is the gravity model.17 The gravity model

predicts that the volume of trade between two countries is directly proportional to their

economic masses, usually measured by GDP or GNP, as well as other variables that

may promote trade, and is indirectly proportional to distance and other obstacles to

trade. We specify the gravity relationship as a panel. Since we are only interested in the

effect of standards on trade volumes, this allows us to absorb all factors that are

constant for each country-pair and year in fixed effects. Since the usual gravity model

variables like GDP, population and colonial ties are constant for each country-pair and

year, they are compounded in these fixed effects.18 As Frankel et al. (1997) point out,

this is the preferred specification. In a monopolistic competition model based on

Krugman (1980), they show that it is required to normalize for growth in real gross

world product. The panel specification accounts for global inflation and growth, which

are also captured in the fixed effects.19 Our first specification estimates the effect of

17 Rauch and Trindad (2002) even claim that it is the only successful empirical framework for predicting trade flows between countries.

18 The country-pair-year fixed effects in our estimation also absorb the multilateral resistance terms derived in Anderson and van Wincoop (2003).

19 See Hummels and Levinsohn (1995) for a more detailed discussion on fixed effects estimation of gravity relationships.

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shared standards (SST) on trade volumes. As in the gravity literature, we estimate our

equation in logs20:

ln(Vijkt) = + ln(SSTijkt) + Fijt + ijkt [1]

where V is the bilateral dollar flow of trade (normally referred to as trade-volume)

between country i and j, t is the time-period, k is a four-digit SITC-industry, SSTijkt is

the number of shared standards in year t, industry k between countries i and j, Fijt

represents the country-pair-year fixed effect that absorbs all factors affecting trade on a

bilateral basis per year that are not industry-specific, such as the gross national products

and distance, and ijkt is an error term.

Since there are concerns that omitted industry-specific relative price effects

could bias the estimates of , the country-pair-year fixed effects are replaced by

country-pair-year-aggregate industry fixed effects. In this specification, every two-digit

SITC industry has a separate fixed effect for each year and country-pair. An omitted

variable bias may result from the fact that technological change varies across industries,

affecting trade-volumes in a way correlated with the number of shared standards.21

Industry time trends control for technological progress and therefore eliminate that

potential source of bias. Our second specification therefore reads as:

20 We follow Eichengreen and Irwin (1998) and add one to the variables in our data before we take logs. This is necessary since there exist numerous zero values for standards in particular industries and countries.

21 Another source of bias may results from the fact that large industries simply have large numbers of standards. Industry dummies can control for that source of bias. Regression results that additionally include four-digit industry dummies are very similar to those presented in section five and are available from the author on request.

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ln(Vijkt) = + ln(SSTijkt) + Tk + Fij(2k)t + ijkt [2]

Tk is a four-digit industry time-trend, and Fij(2k)t is the fixed effect per country-pair-year

and two-digit industry, where the latter is represented by (2k).

Equations [1] and [2] model the effect of shared standards on the total volume of

trade. However, the theories also offer interesting predictions about the relationship

between shared standards, country-specific standards of exporters and importers and the

volume of imports. Our third specification is analogous to [1] and can be written as:

ln(IMijkt) = + 1ln(SSTijkt) + 2ln(CSTEijkt) + 3ln(CSTIijkt) + Fijt + ijkt [3]

IMijkt are the imports from country j to country i in industry k at time t. CSTE is the

country-specific stock of standards in the exporting country, and CSTI is the country-

specific stock of standards in the importing country, again counted per industry and

year. All influences on imports that vary across country-pairs and years but not across

industries are compounded in the fixed effects Fijt. These are, as before, GDPs of the

exporting and importing country, distance, and other factors that can promote or reduce

imports. The same concerns about bias are present in [3]. Therefore, our fourth

specification is analogous to [2]:

ln(IMijkt) = + 1ln(SSTijkt) + 2ln(CSTEijkt) + 3ln(CSTIijkt) + Tk + Fij(2k)t + ijkt [4]

again, Tk is a four-digit industry time trend, and Fij(2k)t is the fixed effect per country-

pair-year and two-digit industry, where the latter is represented by (2k).

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4. DATA DESCRIPTION

The data on trade flows were obtained from the World Trade Database of

Statistics Canada for the years 1985-1995 for 471 four-digit SITC industries. National

accounts and exchange rate data were gathered from the IMF International Financial

Statistics Yearbook.

The main effort involved gathering data on standards and forming a

concordance with the industries in the trade flow data base.22 The German Deutsches

Institut fr Normung (DIN) together with the French Association Franaise de

Normalisation (AFNOR) and the British Standards Institution (BSI) publish documents

on 520,000 individual standards, standards drafts and technical rules for 16 countries in

a database called PERINORM. 280,000 of these documents are standards.23 Slovakia

and the Czech Republic were omitted from the sample since trade data were not

available. Another issue is whether to include the U.S. and Japan in the sample.

Comparison with other sources indicate that the data on the standards of Japanese and

American producers are incomplete. On the other hand, Blind et al. (1999) argue that

the most important standards from these countries have been included. Accordingly, we

expect the standards of these countries that are included in our data to have a stronger

effect than average standards and estimates consequently to be biased away from zero.

Therefore, the US and Japan were also omitted from our sample.24 Table 2 lists the

total number of standards in the PERINORM database, the numbers of standards that

22 Some information about the issues involved are provided in Appendix B. A detailed description of the construction of the database and the concordances can be found in Moenius (1999)

23 See table 2.

24 As a robustness-check, most of the regressions reported were also repeated including those two countries. Qualitative results did not change, as one should expect.

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are concatenated with SITC-industries, and information on health- and environment-

standards by country. For comparison, the counts of documents for the US and Japan

are also included in this table.

Recall from above that our unit of measurement is a count of the number of

documents. Generally, each standard is published in one separate document. Each

document contains information on the country of origin, an industry classification code,

when it was introduced and withdrawn and a list of documents it is linked to

internationally. Documents were counted so that for each country, industry and year,

the stock of standards as listed in the original database was identified. Moreover, links

between documents were counted as bilaterally shared standards.

There are a few important limitations to the data. First, documents differ in their

informational content: the length of the documents varies from one page to several

hundred pages. Second, standards are not equally important economically: it is likely

that using the same voltage in two countries is more important for trade then using the

same door handles. The counts of standards employed in the estimation below do not

allow for any evaluation of their informational content, let alone for their economic

importance. Third, as argued by Casella (1997), standards in the process of European

Unification are not always motivated by economic considerations but are imposed on

new members in order to get access to the "Club". In some pathological cases,

standards have been enforced on countries that were membership-candidates although

they provide no economic benefit to them.25 Finally, there is no clear rule from which

25 Iceland, for example, which is not in our sample though, had to accept the European Railroad Standards in their effort to become a candidate for membership in the EU, although there is no railway system in Iceland.

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to judge whether the original data are of sufficient quality, especially in earlier years26

and specific countries.

5. ESTIMATION RESULTS

This section presents empirical evidence on whether country-specific standards

of importers are a barrier to trade and consequently whether shared standards promote

trade. First, the less controversial claim that shared standards promote trade is investi-

gated. Recall that the measure of shared standards is a count of bilateral links between

documents. Bilateral trade-volumes are regressed on counts of shared standards. Then,

we investigate the effect of country-specific standards on import volumes. Imports are

regressed on the counts of shared standards and country-specific standards of importers

and exporters.

5.1 Shared Standards and Trade Volumes

First the basic relationship between shared standards and trade volumes is

established. Regression results for the basic relationship are reported in table 3. They

confirm the theoretical prediction that trade volumes are higher if countries share more

standards. The first column reports the estimated coefficients of the basic model: trade-

volumes defined as the sum of bilateral exports and imports are regressed on the counts

of shared standards and country-pair-year dummies. The dummies absorb country-pair

26 The earliest Standard listed in the PERINORM database dates back to 1812. But of course, not all standards that ever existed are listed in there. The sample period from 1980 to 1995 was chosen based on the fact that ample data on previously active, but now withdrawn or replaced standards was included since the mid-seventies, which hints at a tolerable degrees of completeness in the 1980s. Moreover, the care regressions only use data from 1985-95, and data from 1980-84 is only used to construct instruments. Finally, Swann et. al also just use data from a previous version of the same database starting in 1985.

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specific effects like common language, shared border, and distance as well as year-

specific factors such as the exchange rates and GNPs of the pair of countries. On

average, a one percent increase in the number of bilaterally shared standards results in a

one-third of one percent increase in trade-volume. In the next column, the country-pair-

year dummies are replaced by country-pair-year-two-digit industry dummies. This is to

partial out any potential bilateral industry-specific relative price effects, under the

assumption that these price effects are identical on the 2-digit SITC level for each

country-pair. At the same time, some of the influence of shared standards will be

absorbed by this additional dimension in the dummy-variable set. The results reported

confirm this prediction: the coefficient on shared standards is somewhat lower than in

the previous column, but still highly statistically significant. A final issue is that

industry-specific technology effects may induce potential bias. Therefore, a separate

time-trend for each four-digit SITC-industry is added. Of course, again it is to be

expected that some of the effect caused by shared standards will be compounded with

the technology effects in the dummy-variables. The results in column three reveal that

the estimated coefficient is still highly significant but is now much smaller.

Trade-data is highly persistent (and so is data on standards) and auto-correlation

is likely to be present. With auto-correlation, test-statistics are incorrect and the esti-

mation is inefficient, though the coefficient estimates are unbiased and consistent.

Column four reports the results with the dummy-variable set of the first column and an

added lagged dependent variable. The coefficient is reasonably close to the one in the

first column, confirming theoretical predictions of auto-correlated data. The t-statistic

on the measure of shared standards falls, but is still highly significant. Column five

repeats the exercise of column three with a lagged dependent variable, with similar

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results. We conclude that shared standards play a statistically significant role in

promoting trade.

How economically important are these results? If we assume an average elasti-

city of 0.34 for all countries over time, then a one percent increase in bilaterally shared

standards between the US and its trading partners would increase US trade volume by

about 6 Billion Dollars.27

How much of an increase in trade can be achieved by harmonizing product and

process standards? Excluding Japan and the US, table 4 reveals that total amounts of

shared standards by country vary by a factor larger than 6. It is certainly wrong to

claim that Australia, which has the lowest count of shared standards, could double its

trade volume if it adopted the amount of shared standards of France, the country with

the highest counts of shared standards. However, the econometric evidence does indi-

cate that there might be room for increasing trade-volumes through harmonization for

some countries.

27 Estimation of separate coefficients for the countries studied reveals that there is considerable variation: coefficients assume values between 0.06 and 0.49. The estimated coefficient of 0.34 can still be interpreted as an average effect.

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5.2 Estimation Results for the Import-Equation

This part repeats the econometric exercise for imports only, this time including

the number of country-specific standards of the importer and exporter as additional

regressors. The surprising result is that country-specific standards in importing coun-

tries promote trade on average. They hinder trade only in non-manufacturing industries

like agriculture. In manufacturing, they increase imports.

The Basic Relationship

This time, imports per industry and year for each country pair are regressed on

the number of shared standards, the number of country-specific standards of importers

and exporters and a set of dummy-variables.

The dummy-variables serve the same purposes as described above. Therefore,

we do not repeat this discussion. The results are reported in table 5. As column one

indicates, a one percent increase in the number of bilaterally shared standards results in

a one-quarter percent increase in the volume of imports. An increase in the number of

country-specific standards of the exporter increases the volume of trade. This finding is

supportive of the claim that country-specific standards raise the competitive advantage

of an industry. One of the most interesting finding of this paper, though, is that even

the country-specific standards of importers have a positive coefficient. As can be seen

from column 2 - 5, the regression results are robust again to country-pair-two digit-

industry fixed effects, additional four-digit-industry-time trends and lagged dependent

variables.

We conclude that shared standards play a statistically significant role in pro-

moting trade, as do country-specific standards of the exporter. Moreover, we reject the

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hypothesis that country-specific standards of importers are a barrier to trade on average.

We offer an explanation for this counterintuitive result in section 6.

The Variation across Industries

The econometric exercise of the previous section was also undertaken for each

one-digit SITC industry separately. Results are reported in table 6. The first obser-

vation is that coefficients exhibit large variation across industries, indicating that pool-

ing restrictions can be decisively rejected. Nevertheless, the pooled results are valid if

interpreted as averages. Next, there are negative coefficients on shared standards for

food, beverages, crude minerals and oils, but positive coefficients on shared standards

for all other industries. Third, country-specific standards of exporters promote trade in

most industries independently of the type of industry. Finally, and most interestingly,

country-specific standards of importers exhibit negative effects in manufacturing of less

complex goods (0-3). They have positive effects in industries producing more complex

goods (5-8).

Endogeneity

All presented estimates suffer from the potential problem that the direction of

causality may be reversed: large trade volumes may spur harmonization efforts

internationally to reduce barriers to trade. They may also increase standardization

nationally to facilitate domestic coordination. On the other hand, strong import

competition of less competitive industries may lead to higher standardization for

protectionist purposes. A common way to treat endogeneity is with instrumental

variable estimation. Generally, it is hard to find instruments on a country-pair-industry

level. We exploit an institutional regularity in combination with the large size of our

19

data set to construct these instruments. All standards institutes review their standards

approximately every five years.28 Standards that are no longer needed are removed,

those who proved to be inadequately specified are altered according to current

requirements. Under the assumption that this review process is effective, then after five

years all standards that were introduced based on short-run considerations (if any) are

eliminated and there are only standards listed that meet the purposes of economic

actors. Consequently, current error terms are unlikely to be correlated with

standardization activities that date back more than five years. We therefore use our

standards measures lagged five years as instruments for the estimation process. Using

the results from table 6, we estimate the coefficients for industries with one-digit SITC

codes from 5-8 separately. The results are presented in table 7. We report the standard

OLS results with country-pair-year dummies for the years 1985-1995 in the first two

columns and the corresponding IV results in column three and four.29 We first note that

the general pattern of the previous tables remains unchanged both with- and without

instrumental variables. Since coefficients are very precisely estimated, it seems that

OLS estimates are slightly biased towards zero. Overall, we find that instrumental

variable estimation does not change the previously observed pattern. While

endogeneity-bias may be present, it does not seem to affect the qualitative character of

our results.

28 Interviews that I conducted with representatives of standards institutes in Germany, the Philippines, Japan, Vietnam and Thailand between 1999 and 2004 revealed that this procedure is not only institutionalized by the major standards bodies, but is also implemented by smaller institutes.

29 The described patterns are very similar for the specifications with lagged dependent variables and as well as country-pair-year-two-digit industry dummies and are available from the author on request.

20

6. RECONCILING THE EVIDENCE WITH ECONOMIC THEORY

Reviewing the predictions of the literature, it can be noted that none of the theo-

ries can explain the findings of this paper, though some of the theories explain part of

the story. In this section, we offer an alternative explanation for the empirical regulari-

ties in the data.

The theory of non-tariff barriers to trade in its mainstream form predicts positive

coefficients on shared standards and negative coefficients on country-specific standards.

Whenever we find positive coefficients on shared standards, we almost always also find

positive coefficients on country-specific standards of importers. When we find negative

coefficients on the latter, we also find negative coefficients on shared standards. Our

empirical evidence appears to contradict the main stream theory. On similar grounds,

the competitive disadvantage and standardization trap theories can be rejected as only

part of the story, at best.

The competitive advantage theory correctly predicts a positive coefficient on the

number of country-specific standards of exporters. Its second prediction is that the

coefficient on the country-specific standards of importers should be negative. The

econometric results indicate that this only holds true for non-manufacturing industries,

though one would expect that the competitive advantage theory would be most relevant

for manufacturing industries. In manufacturing, however, we find a positive coefficient

on the country-specific standards of importers. We conclude that this theory does not

offer comprehensive explanation of the empirical observations.

The loss of variety approach seems to have some explanatory power for specific

non-manufacturing industries. Recall though that it also predicts that country-specific

21

standards of both importers and exporters are trade-promoting, which is not the case in

the industries where we find negative coefficients on shared standards.

We conclude that none of the existing theories really provides an acceptable

overall explanation for our empirical results. On the other hand, the particular structure

of the results suggests a different explanation, based on information imperfections and

adaptation costs.

Imagine a two-country world without any standards. In each of the countries

there are low-tech and high-tech industries. If a country wants to export to the other

country, it has to research the technical specifications and preferences that prevail in the

other country. Then it has to modify its domestic products to adapt them to the foreign

market. Both processes are costly. I will refer to the first type of costs as information

costs and the second type as adaptation costs. It seems likely that information costs

increase with the technical sophistication of the industry.

Now let us assume both countries introduce country-specific institutional stan-

dards. Since these standards are well-documented and easily accessible, firms do not

need to gather information on technical specifications and preferences in the market,

thereby reducing search costs. Moreover, instead of compiling information on different

varieties, it is sufficient to have access to the predominant specification, the standard.

This reduces the total amount of information that needs to be collected. As a conse-

quence, information costs fall. We follow the common assumption that adaptation costs

rise due to the introduction of country-specific standards.30 Trade-volumes will

30 The assumption of rising adaptation costs is also confirmed by the survey mentioned above, see Bahke (1999). The consequences for constant or falling adaptation costs are similar and can be argued along the same lines. However, there is no possibility to distinguish between the impact of information costs and product adaptation costs if the latter also fall.

22

increase if the reduction in information costs outweighs the increase in adaptation costs.

If the two countries decide to share some of their standards, this should increase trade

even more, since now adaptation costs are also dramatically reduced.31 Finally,

importers can gather more information about the quality of exporters if the exporters

use a large number of their country-specific standards, as argued by Jones and Hudson

(1996). All that is required is that importers and exporters have mutual access to their

respective trading partners country-specific standards. Therefore, even country-spe-

cific standards of exporters should increase trade. This model explains why we find

that all three coefficients are positive.

If informational requirements are small, then the increase in adaptation costs due

to the adoption of standards may outweigh the reduction of informational costs. In this

case, we expect to see a negative coefficient on country-specific standards of importers.

Reductions in variety may lead to negative coefficients on shared standards.

The information gathering costs described above are fixed costs. Product adap-

tation costs will likely also have a fixed component. The average costs of these two

combined decrease with the volume of imports. Therefore the effect of importers

country-specific standards should increase with importers market size. On the other

hand, there is no real clear prediction for interactions of country-size with the other

standards-variables. We investigate this hypothesis by including terms that interact the

measures of standards with the size of the importer and exporter countries, as measured

by GDP. The results are reported in table 8. The coefficient on the interaction term we

are interested in is positive, as predicted. All other coefficients on interaction terms are

also reported. The results are consistent with our argument that the interaction of

31 Again, the DIN-survey offers support for this claim (Bahke 1999).

23

adaptation and transaction costs plays a significant role in understanding the effects of

standards on trade. Future research will determine whether this preliminary argument

withstands more rigorous analysis.32

How do these findings relate to other empirical studies? Two branches of the

literature should be considered. As noted above, Harrigan (1993) found that non-tariff

barriers to trade are small and in some cases are even trade promoting. Although this is

consistent with the results of this paper, our methodologies are dissimilar. In the analy-

sis of this paper, we include only a subset of the factors that Harrigan measured as

NTBs. Moreover, while we find clear differences between manufacturing and non-

manufacturing industries, there is no pattern in his results. Finally, his measures are

coverage-ratios (percentages of imports in an industry that are ruled under a certain

NTB) of products, while the measure employed here uses counts of documents.

Three other papers (Swann et al. 1996, Blind et al. 1999, Blind 2001) examine

the PERINORM database, which is the original source of our information on bilateral

standards. These authors distinguish between country-specific and international

standards, but they do not measure whether the standards are shared on a bilateral basis.

They each only study pairs of countries, e.g. trade of the United Kingdom with

Germany. Finally, the data set used in this study is about 1,000 times larger.

Nevertheless, some results can be usefully compared.

Swann et al. (1996) also find that both international and country-specific stan-

dards promote imports into the United Kingdom. Blind et al. (1999) study the effects of

32 The model of Fischer and Serra (2000) includes a fixed cost of product adaptation. The results in table 8 are consistent with Lemma 1 in their paper. Product adaptation costs can also be interpreted as the degree of compatibility as in Barrett and Yang (2001).

24

standards on German imports, exports and trade-balances.33 They find that country-

specific German standards hinder imports, while international standards promote

imports. While the former study finds results that are similar to the ones presented here,

the latter study seems to contradict the results of this paper. It should be noted that both

of the previous studies investigate country-pairs only, not a multi-lateral data set, and

also use different measures for standards. Therefore we do not interpret these results as

contradictory to ours. But since Swan et al. (1996) and Blind et al. (1999) use exactly

the same methodology, it is rather these two that contradict each other. The data set

presented in this paper allowed us to further investigate the contradicting results of the

two studies and to offer a solution to the puzzle.

7. CONCLUDING REMARKS

This paper gathers empirical evidence that sheds light on theoretical claims that

country-specific standards of importers are trade inhibiting and therefore that shared

standards promote trade. The evidence suggests that trade barriers induced by dissimi-

lar standards are prevalent in non-manufacturing industries, but in manufacturing,

country-specific standards tend to promote international trade. This evidence is con-

sistent with a transaction costs argument based on incomplete information: the absence

of standards imposes high information costs on trading partners, while standards lower

information costs, even if they are specific to one country. If the costs of adapting

products to foreign markets are small relative to information costs, a positive effect of

33 Similarly, Blind (2001) investigates the role of standards and innovation for trade in measure- and testing instruments in Switzerland. Other attempts to estimate the effect of standards and technical barriers on trade, especially in certain sectors relevant for development were driven by a large research project by the World Bank. For example, see Maskus and Wilson (2001) or Otsuki et al. (2001).

25

local standards of importers results. Under the assumption that transaction costs are

greater in industries that are more technologically sophisticated, country-specific stan-

dards are more important for manufacturing industries. This prediction is supported by

our empirical results.

26

APPENDIX A: TABLES

Table 1 Predictions of the Theoretical Literature

Shared

Standards

Country-

specific

Standards

Importer

Country-

specific

Standards

Exporter

Main-stream/strategic alliances + - Competitive Disadvantage + -

NTBs

Standardization Trap + - - Competitive Advantage - + Loss of Variety - + +

27

Table 2:

Countries and Number of Documents in the PERINORM Database

Country

Number of Standards in PERINORM

Number of

Standards in Concordance

with SITC

Number of Health-Stan-dards in Con-cordance with

SITC*

Number of Environmental Standards in Concordance with SITC*

Austria 9,286 5,191 28 39

Australia 10,389 5,460 12 9 Belgium 8,276 3,994 18 19

Switzerland 13,388 8,345 44 24 Germany 47,294 28,939 38 40

Spain 20,240 12,126 41 44 France 40,934 22,958 57 60

Great Britain 27,597 16,304 36 53 Japan 13,804 6,197 1 7

Netherlands 24,837 11,961 111 89 Norway 7,600 4,128 23 21 Poland 18,714 13,012 14 45 Turkey 18,427 12,565 75 57

US 21,130 12,117 6 21 Sum 281,916 163,297 504 528

* Counts of health and environmental standards are obtained based on standards-classification codes (ICS) 01.040.13 and 13-13.340.99 in the PERINORM database. See Moenius (1999) for details.

28

Table 3: Trade Volumes on Shared Standards Regressand: Trade Volume by Four-Digit SITC from 1985-95

Regressors

Shared standards 0.34 (84.39) 0.24

(47.98) 0.12

(23.43) 0.26*

(15.88) 0.095* (6.68)

Lagged Dependent Variable

0.88 (702)

0.81 (500)

Country-Pair-Year Fixed Effects Yes Yes

Country-Pair-Year- Two-digit Industry- Fixed Effects

Yes Yes Yes

Four-digit Industry Time-Trend Yes Yes

Observations 263,484 263,484 263,484 227,799 227,799 The robust t-statistics of each coefficient estimate are reported in parentheses.

* Coefficients of Estimation with lagged dependent variable where transformed according to the for-

mula 1 , where is the coefficient to be transformed and is the coefficient on the lagged depen-dent variable

29

Table 4 Number of Shared Standards by Country in 1993 Country Number of

Shared Standards

Australia 11,791 Austria 18,554 Belgium 40,919 France 71,024 Germany 66,908 Netherlands 36,805 Norway 16,339 Poland 19,606 Spain 27,855 Switzerland 36,039 Turkey 19,449 United Kingdom 68,921 Mean 36,184 Standard deviation 21,693 Report only: Japan 6,236 United States 6,972

30

Table 5: Imports on Shared and Country-Specific Standards Regressand: Imports by Four-Digit SITC from 1985-95

Regressors


(14.55) 0.11

(20.67) 0.25*

(14.38) 0.010* (6.81)

Country-specific standards importer

0.073 (17.27)

0.19 (36.64)

0.12 (22.29)

0.13* (7.30)

0.13* (8.39)

Country-specific standards exporter

0.32 (76.62)

0.20 (39.30)

0.13 (24.41)

0.32* (18.89)

0.13* (9.26)


0.88 (951)

0.77 (574)

Country-Pair-Year Fixed Effects Yes Yes


Yes Yes Yes

Four-digit Industry Time-Trend Yes Yes

Observations 503,356 503,356 503,356 433,238 433,238 The robust t-statistics of each coefficient estimate are reported in parentheses.



31

Table 6: Imports on Standards by Industry Regressand: Imports by Four-Digit SITC from 1985-95

Regressors SITC

Shared Standards

Country-Specific

Standards Importer

Country-Specific

Standards Exporter

Adjusted R2 Number of Observations

0 Food -0.11 (-4.74) -0.13

(-8.30) 0.18

(11.52) 0.39 72,916

1 Beverages -1.27 (-13.69) -1.29

(-17.78) -0.21

(-3.01) 0.41 8,758

2 Crude Materials

-00.2 (-0.11)

-0.045 (-3.21)

0.097 (7.04) 0.23 57,286

3 Mineral Fuels 0.28 (5.12) -0.25

(-5.28) 0.48

(11.37) 0.36 11,688

4 Oils -0.16 (-1.28) 0.055 (0.93)

-0.12 (-2.43) 0.37 7,050

5 Chemicals 0.14 (10.05) 0.17

(13.34) 0.38

(32.28) 0.54 46,618

6 Manufacturing by Material

0.010 (1.35)

0.10 (12.63)

0.093 (11.23) 0.48 125,420

7 Machinery 0.16 (18.16) 0.23

(25.15) 0.25

(26.80) 0.60 93,108

8 Misc. Manufacturing

0.27 (24.48)

0.074 (7.67)

0.41 (43.61) 0.57 74,238

9 Else (none) -0.11 (-1.56) 0.50

(9.35) 0.21 4,274

The robust t-statistics of each coefficient estimate are reported in parentheses. Each estimation equation includes Country-Pair- Year Fixed Effects

32

Table 7: Imports on Shared and Country Specific Standards: Instrumental Variable Estimation Regressand: Imports by Four-Digit SITC from 1985-95

OLS IV OLS IV

Direct Effects


(49.31) 0.14

(12.37) 0.14

(10.21)


0.07 (17.27)

0.06 (12.02)

-0.20 (-23.62)

-0.22 (-23.29)


0.32 (76.62)

0.28 (63.87)

0.30 (34.50)

0.32 (34.11)

Interaction Terms: Standard-Type Dummy for Complex Goods: Shared standards -0.009 (-0.76)

0.073 (4.74)


0.30 (31.18)

0.31 (28.52)


-0.076 (-7.78)

-0.14 (-12.89)

Complex Dummy 1.54 (154) 1.54 (150)

Country-Pair-Year Fixed Effects Yes Yes Yes Yes

Observations 503,356 501,952 503,356 501,952 The robust t-statistics of each coefficient estimate are reported in parentheses. Data fro instruments ranges from 1980-90

33

Table 8: Imports on Standards Interacted with Country Size Regressand: Imports by Four-Digit SITC from 1985-95

Direct Effects

Shared standards 0.061 (1.93) -0.048 (-1.09)

0.037* (0.27)

-0.39* (-2.29)


-0.29 (-13.62)

0.12 (3.68)

-0.22* (-2.12)

0.24* (1.73)


0.49 (23.70)

0.18 (5.71)

0.64* (6.58)

0.24* (1.83)

Interaction Terms: Standard-Type IM-country-GDP: Shared standards 0.020 (5.99)

0.015 (3.18)

0.024* (1.74)

0.043* (2.59)


0.058 (22.44)

0.010 (2.62)

0.070* (6.08)

0.013* (0.87)


-0.057 (-22.07)

-0.004 (-0.92)

-0.082* (-7.25)

-0.020* (-1.39)

Interaction Terms: Standard-Type EX-Country-GDP: Shared standards -0.05 (-1.47)

-0.007 (-1.44)

-0.011* (-0.73)

0.015* (0.78)


0.001 (0.45)

-0.006 (-1.48)

-0.017* (-1.37)

-0.024* (-1.42)


0.018 (6.95)

0.003 (0.73)

0.018* (1.61)

0.015* (0.94)


0.88 (972)

0.84 (701)

Country-Pair-Year Fixed Effects Yes No Yes No


No Yes No Yes

Adjusted 2R 0.39 0.57 0.86 0.87

Observations 526,968 526,968 455,598 455,598 The robust t-statistics of each coefficient estimate are reported in parentheses.



34

APPENDIX B: DATA CONSTRUCTION

The original data source is PERINORM (1998). It contains information of about

520,000 documents, 300,000 of which are standards. Fields in the original data table

include country of origin, an industry classification code, dates introduced and with-

drawn, information about related documents, and international links. A detailed

description of the steps involved to construct the data set used in this paper can be

found in Moenius (1999). Some of the major issues are listed here.

- A standard was counted as active from the year introduced until the year it expired, regardless of the

month it was introduced or withdrawn. If no expiration date was provided in the original database, it

was assumed active.

- Expired documents frequently had no industry classification codes that form the basis for the concor-

dance with SITC industries. These were recovered from related documents, like consecutive docu-

ments or previous drafts, if this information was available there.

- Some documents had expiration dates but no dates when they were introduced. In this case, it was

assumed that they existed for five years, since standards are normally reviewed at this interval.

- Many standards had multiple classification codes at different levels of specificity attached to them,

similar to one-digit versus two- or three-digit classifications of industries. Unique classification

codes are necessary to avoid double counting within the same industry. Only the most specific

classification listed with a standard was accepted. If there were multiple classifications at the same

level of specificity, the unique classification was chosen randomly.

- Shared standards frequently had differing classification codes across countries. The unique classifica-

tion was then determined by a majority rule: if more than one country listed this standard, the clas-

sification code that was used by the majority of countries was also used for classifying the shared

standard.

- If a standard had links to documents in other countries, these links were in most cases not bilateral,

but only referred to a European or International standard. For example, a French standard just had a

link to an ISO-standard. This ISO-standard then listed links to standards in Belgium, Germany and

35

Spain. In this case, the link from the French standard to the ISO standard was replaced with the links

from the French standard to the related documents in Belgium, Germany and Spain.

- Frequently, international links were not symmetric. For example, documents in the Netherlands,

Poland and Turkey reported links to an ISO standard. The ISO standard, however, just reported links

to Norway, Poland and the United States. All of these links were updated so that each of the docu-

ments in the countries had the full number of links. The standard in Norway, e.g., then had the links

listed to the Netherlands, Poland, Turkey and the United States.

36

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40

ABSTRACT1. INTRODUCTION2. THEORETICAL FRAMEWORK2.1 What Are Standards?2.2 Previous Research

3. EMPIRICAL SPECIFICATIONS4. DATA DESCRIPTION5. ESTIMATION RESULTS5.1 Shared Standards and Trade Volumes5.2 Estimation Results for the Import-EquationThe Basic RelationshipThe Variation across IndustriesEndogeneity

6. RECONCILING THE EVIDENCE WITH ECONOMIC THEORY7. CONCLUDING REMARKSAPPENDIX A: TABLESRegressorsRegressorsRegressorsSITCDirect EffectsDirect Effects

APPENDIX B: DATA CONSTRUCTIONREFERENCES