R&D, market structure and appropriability in the Brazilian manufacturing.
Recent studies suggest that firms use not only patents but a mix of appropriability nachanisms (MAM) as R&D protection strategy. This paper presents empirical evidence on the relationship between R&D, market structure and a mix of appropriability mechanisms in Brazilian manufacturing firms. Our results suggest that market share and MAM increase firm's R&D likelihood.

Keywords: R&D, market structure, appropriability, Brazilian manufacturing

JEL codes: L10, L21, 032

Article Type:
Industrial research (Analysis)
Industrial research (Brazil)
Manufacturing industry (Management)
Silva, Gilson Geraldino, Jr.
Pub Date:
Name: Journal of International Business and Economics Publisher: International Academy of Business and Economics Audience: Academic Format: Magazine/Journal Subject: Business, international; Computers Copyright: COPYRIGHT 2011 International Academy of Business and Economics ISSN: 1544-8037
Date: Dec, 2011 Source Volume: 11 Source Issue: 4
Event Code: 200 Management dynamics Computer Subject: Research and development; Company business management
Product Code: 8511000 Research & Development-Industry; 8500000 Science, Research & Development NAICS Code: 54171 Research and Development in the Physical, Engineering, and Life Sciences; 5417 Scientific Research and Development Services SIC Code: 8731 Commercial physical research
Geographic Scope: Brazil Geographic Code: 3BRAZ Brazil
Accession Number:
Full Text:

Traditionally, empirical R&D-market structure analyses are at the industry level, and disaggregation varying from 2 to 5 SIC digits, using patents of invention as appropriability mechanisms (Lee (2005), Arora (2008)). Cohen (2010) reviews recent studies and remarks how modern data bases and panel analyses fill in the gaps in the previous literature. Cohen and Levin (1989) and Cohen (2010) build a sound literature review about this subject. On the other hand, Cohen, Nelson and Walsh (2000) and Hall and Ziedonis (2001) show us that firms use a mix of appropriability mechanisms (MAM).

In this paper we display empirical evidence about the relationship among R&D, market structure and mix of appropriablility at the firm level in Brazilian manufacturing. This allows us take account of more fundamental sources of variation in the innovative behavior and performance of firms and industries using firm level appropriability mechanisms. It is possible thanks to two detailed surveys conducted by the Brazilian Census Office (IBGE): the Industry Annual Survey (PIA) and the Technological Innovation Survey (PINTEC).

Our empirical results suggest that market share and MAM increases firm's R&D likelihood. As far we know, this is the first empirical study in this field to examine Brazil and one of the few to look at firm level data.

This paper has 3 remaining sections: section 2 reviews patens limits and mix of appropriability mechanisms importance; section 3 shows data base and variables; section 4 shows our econometric results; and section 5 conclusions.


There are limits to using patents as an appropriability indicator. At least since Scherer (1965) we have known that a straight count of patents has two limitations: (1) the propensity to patent an invention of given quality may vary from firm to firm and from industry to industry; and (2) the quality of the underlying inventions varies widely from patent to patent.

Nowadays it is clear that not only patents but also others intellectual protection tools have positive effects on the economy. Copyright laws, for example, incentivize technological innovation and allow better price discrimination in the US VHS and DVD market (Mortimer, 2007).

In fact, intellectual protection through patents is not always the best option for many firms. Cohen, Nelson and Walsh (2000) try to explain why some American companies register patents and others not. Analysing data from 1478 R&D labs in the American manufacturing industry in 1994, they found that firms protect their innovation profits not only through patents but also using a mix of intellectual property mechanisms, which include industrial secret and leading time. Among those mechanisms, patents are the fewest used while industrial secret and leading time are the most common.

Hall and Ziedonis (2001) agree with Cohen, Nelson and Walsh (2000): patents are not always the best option. In some cases there is a patent paradox, as illustrated by their empirical study of 95 firms' pattern standards in the US semiconductor industry between 1979 and 1995--an industry whose main characteristic is fast technological change and cumulative innovation. The results show that those firms don't always use patents to protect their R&D profits--which is a paradox in a high and fast technological change sector.

While patents sometimes are not the best option in developed countries, data limitations make developing countries a less than ideal source of information about innovation. In general, data on patents have three important restrictions: i) they measure inventions not innovation, ii) patent standards change according to country, industry and process and iii) companies frequently use alternative protection tools such as industrial secret and leading time (Gorodnichenko, Svejnar and Terrell, 2008).

At the least, we should note that besides many formal and informal apropriability mechanisms, such as patents and designing, advertisement1 is a protection option that is sometimes far more efficient than formal ones.

In fact, if choosing between registering an innovation in a patent office or showing it to as many potential buyers as possible, the second option could be financially better than the first one. And once an innovation is associated with a company, competitors will have extra difficulty because when they imitate or create, they will need to persuade potential buyers that their products are as good as or better than those from companies which first innovated and advertised it.

Advertising may serve as a signal of product quality or R&D effort; or it may be that both R&D and advertising are strategic investments and thus affect each other. The relationship between advertising, R&D, and market structure advertising increase perceived quality (Shaked and Sutton, 1987).


Our data is taken from the Industrial Annual Survey (Pesquisa Industrial Anual, PIA) and the Technological Innovation Survey (Pesquisa de Inovacao Tecnologica, PINTEC), both produced by Brazilian Census Office (Instituto Brasileiro de Geografia e Estatistica, IBGE). PIA is a firm level industrial annual survey to Brazilian manufacturing and PINTEC2 is a firm level technological innovation survey. PIA and PINTEC are connectable through a common firm identification number. We match PIA and PINTEC for years 2003 and 2005 editions and get a short unbalanced panel with 14,000 firms.

TABLES 1 and 2 (that should be read through lines) show us that among 14,379 firms average Market Share (MS) is 0.9%, with standard deviation 3.9% and 75th percentile 1.4%. Average price cost-margin (PCM) is 64%, with median 71%, standard deviation 23.7%, 5th percentiles 23%, and 75th percentile 82%.

Finally, the average advertisement/net revenue ratio (ADV) is 0.3% with median 0.02%, standard deviation 1.2% and 75th percentile 0.3%

To sum up, these descriptive statistics show us that market share is lower than 1.5% for at least 75% of the firms in this sample, and at least 50% of them have price cost-margin larger than 71%. They also show us a significant dispersion for all variables described.

TABLE 3 (that should be read through columns) show us that among five writing protection mechanisms, patents of invention (PI) is used by 6.22% of the firms in our sample, utility model patent (UMP) by 5.47%, industry design register (IDR) by 4.98%, trade marks (TM) by 22.97% and copyright (C) by 2.44%. Among the three strategic protection mechanisms, design complexity (DC) is used by 2.59% of the firms in our sample, industrial secret (IS) by 10% and leading time to competitors (LTC) by 5.74%. Other appropriability mechanisms, which each firm specifies differently, are used by 2.8%.

A firm can at the same time register a patent, have a design complex and spend on advertisement. Hence, it makes sense consider a mix of appropriability methods (MAM). We create MAM qualitative variable that is one to firms that used more than one appropiability mechanism, include advertisement, and 0 on the contrary. 49.74% of the firms in this sample used a mix of appropriability methods.


4.1. Econometric model

Because our R&D dependent variable is a binary one, we use a binary response model. Probit is the binary response models most commonly used in applications. It is typically estimated by maximum likelihood which has good properties in large samples. In particular, it is asymptotically efficient (Horowitz and Savin, 2001).

Generally, a probit model can specified as

(1) P(Y=1|X) = G(X[[beta].sub.k]) = G([[beta].sub.0] + [[beta].sub.1][X.sub.1]+ (...) + [[beta].sub.k][X.sub.k]), where G(.) is a normal cdf.

The [[beta].sub.k] gives the signs of the partial effect of each [x.sub.k] on the response probability; and the statistical significance of [x.sub.k] is determined by whether we can reject [H.sub.0]: [[beta].sub.k] =0. In sum, the signing of [[beta].sub.k] determines whether the independent variables have a positive or negative effect on the binary dependent variable (Wooldridge, 2002).

However, there is neglected heterogeneity problem. According to Blundell, Griffith and Van Reenen (1999) the empirical relationship between innovation and market share could be artificial because of unobserved heterogeneity deriving from the different technological opportunities and appropriability conditions facing firms and therefore the association could be spurious because of poor data quality.

It is possible that market share and the particular types of appropriability mechanisms may be related to unobserved forces that also drive R&D as a specific kind of unobserved heterogeneity. For example, the dynamics of market shares will depend crucially on the speed and effectiveness of rivals' responses. In this respect, different industries display widely differing characteristics. Many patterns of interaction may emerge between a leader and its rivals, and these patterns will reflect various factors, some of which (such as the beliefs of rival firms, for example), are very difficult to measure, proxy, or control for in empirical studies (Sutton, 2007). On the other hand, the pattern of appropriability varies according to firm's strategy. In some cases it is useful focus on writing mechanisms as in pharmaceutical industry. In other cases it is better strategic mechanisms as industrial secret in high technological sectors. But it is always rational a mix of appropriability mechanism, advertisement inclusive. The mix composition, however, is another source of unobserved heterogeneity.

In fact, omitting variables which are not independent of the included explanatory variables results in biased and inconsistent estimated coefficients. The omitted variables set could have variables such as management ability, technological opportunity and preference for innovation.

The fixed effects probit analysis treats fixed effects as parameters to be estimated along with p. But, treating fixed effects as parameters to estimate lead to potentially serious biases. This doesn't happen if we consider random effects (Wooldridge, 2002; Artes, 2009). There is any specific solution available to unobserved heterogeneity problem and probit random effects sounds the best option in our case.

In the general form our specification is


This can be re-written as


[R&D.sub.it] is a dummy variable (3) to firm i at time t, which is 1 if firms had expended on R&D and 0 otherwise.

[MS.sub.it] is market share (4), [MS.sup.2.sub.it] market share squared, [LNPCM.sub.it-1] and [LNPCM.sub.it-2] are the first and second lags of the log price-cost margin, [MAM.sub.it] is the mix of appropriability mechanisms, [MS.sub.it]*[MAM.sub.it] is the market share-mix of appropriability indicator interaction, and [MS.sup.2.sub.it]*[MAM.sub.it] is a market share squared-mix of appropriability interaction term.

[MAM.sub.it] allows us control for systematic firm differences in appropriability on firm R&D decisions. [MS.sub.it]*[MAM.sub.it] tells us if market structure and appropriability are (or not) mutually independent in their relationship with industry R&D performance, i.e., if it controls the market share effects on R&D firm decision for systematic firm differences in appropriability.

The tension between the often-cited inverted-U hypothesis and the diverse empirical results indicates that the available empirical evidence is inconclusive, and thus much remains to be learned regarding the relationship between market structure and industry R&D performance (Cohen and Levin (1989), Lee (2005), Aghion et al (2005)). [MS.sup.2.sub.it] provides support for the inverted-U hypothesis. And [MS.sup.2.sub.it]*[MAM.sub.it] it allows us check if appropriability strategies influence the inverted-U relationship. Last, Tit is the firm random effect to avoid the neglected heterogeneity problem.

We expect that [[alpha].sub.1], [[alpha].sub.3], [[alpha].sub.4], [[alpha].sub.5], [[alpha].sub.7] will have positive sign as market share, lagged profit and appropriability mechanisms should all have a positive effect on a firm's R&D decision. And [[alpha].sub.2] and [[alpha].sub.6] could be positive or negative as either U or and an inverted-U market share-R&D relationship are possible.

As Artes (2009) remarks, it has been argued that companies that perform R&D are more likely to obtain higher profits in the future, and market structure will shift accordingly. If innovation and market structure are simultaneously determined, the estimation suffer from an endogeneity problem. Previous literature that tested endogeneity between market structure and innovation is contradictory. The problem is difficult to address because there are lags between successful innovations, and the accumulation of profits is able to affect the monopoly power of the company. Furthermore, it seems plausible that the lags vary from firm to firm.

In our sample, firms are observed during a short period of time over which market conditions are unlikely to change in response to firms' innovative activities. In that sense the panel being short could alleviate the possible endogeneity.

A traditional interpretation of the innovation-market power correlation is that failures in financial markets force firms to rely on their own supra-normal profits to finance the search for innovation. The availability of internal sources of funding are useful for all forms of investments, but may be particularly important for R&D. External sources of finance may be more expensive (due, for example, to asymmetric information) and there is the risk that rival firms could acquire valuable information if a firm seeks external funding for its innovation projects (Blundell, Griffith and Van Reenen, 1999).

Our lagged profits capture the fact that past profits can help finance innovation and also helps to avoids endogenity problem, especially because of the simultaneity between R&D expenditure and profitability.

4.2 Regressions results

TABLE 4 show us that market share, lagged profits and mix of appropriability mechanisms (MAM) increase R&D likelihood. There is also a non-linearity R&D-market share relation as [MS.sup.2 ]has negative impact on R&D decision. Market share and MAM is not significant. And market share square and ad interaction keeps sign. Those sings are according to expected.

Those regression results suggests that 1) mix of appropriability mechanisms efficient as R&D protection efforts among Brazilian industrial firms. This makes sense since firms use a intellectual protection portfolio, especially useful in countries with low legal enforcement (Hall and Ziedonis (2001), Cohen, Nelson and Walsh (2000), Gorodnichenko, Svejnar and Terrell (2008)), 2) market share affects positively firm's R&D decision, i.e., market concentration and R&D expenditure are positively correlated in low appropriability sectors, which suggests that market concentration supplements low R&D appropriability or that technological competence (or opportunities) may not be fully exerted (or exploited) when market structure remains atomistic (Lee, 2005), 3) there are non-linearities, with is according to Cohen and Levin (1989), Lee (2005), Aghion et al (2005), 4) lagged profits increase R&D likelihood, probably because of failures in financial markets as Blundell, Griffith and Van Reenen (1999) suggests.


This study presents empirical evidence on the relationship between R&D, market structure and a mix of appropriability mechanisms in Brazilian manufacturing firms. Our results suggest that market share, lagged profits and mix of appropriability mechanisms (MAM) increase R&D likelihood. There is also a non-linearity R&D-market share relation. Those results are according to a couple of recent studies, as Hall and Ziedonis (2001), Cohen, Nelson and Walsh (2000), Gorodnichenko, Svejnar and Terrell (2008), Cohen and Levin (1989), Lee (2005), Aghion et al (2005) and Blundell, Griffith and Van Reenen (1999).

In sum, our results about R&D and market structure not only contribute to the recent debate about this subject, but also highlight the effect of mix of appropriability mechanisms besides patents, especially for an important emerging economy such as Brazil.


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Gilson Geraldino Silva-Jr, Catholic University of Brasilia, Brazil

(1) For an in depth economic analysis of advertisement, see Bagwell (2007).

(2) PINTEC is similar to Spanish Survey of Business' Strategies, but more detailed. For example, PINTEC has information about appropriability mechanisms beyond patents.

(3) Artes (2009) also uses an R&D dummy as dependent variable in a recent R&D-market structure study to Spain.

(4) Market share measures market concentration and firm size at the same time. See Caves and Porter (1978) and Schmalensee (1989).
TABLE 1--continuous variables descriptive statistics

Variable     Observations    Average    Standard Deviation

MS           14379           0.009      0.041
[MS.sup.2]   14379           0.0018     0.023
PCM          14379           0.64       0.237
ADV          14379           0.003      0.012

Source: Our tabulation from 2003 and 2005 PIA and PINTEC surveys

TABELA 2--continuous variables percetiles

Variable      P5        P25       P50       P75       P95

MS            0.0001    0.0007    0.0034    0.014     0.11
[MS.sup.2]    0         0         0         0.0002    0.012
PCM           0.23      0.57      0.71      0.82      0.93
ADV           0         0         0.0002    0.003     0.028

Source: Our tabulation from 2003 and 2005 PIA and PINTEC surveys

TABLE 3--firms that used appropriability protection mechanisms

(%)       PI        UMP       IDR       TM        C         DC

Yes       6.22      5.47      4.98      22.97     2.44      2.59
No        93.78     94.53     95.02     77.03     97.56     97.41
Total     100.00    100.00    100.00    100.00    100.00    100.00

(%)       IS        LTC       others    MAM

Yes       9.99      5.74      2.80      49.74
No        90.01     94.26     97.20     50.26
Total     100.00    100.00    100.00    100.00

Source: Our tabulation from 2003 and 2005 PIA and PINTEC surveys

Table 4 : R&D, mix of appropriability and market structure--probit
panel regressions


CONSTANT                           -2.26(0.072) ***
MS                                 10.42(1.80) ***
[MS.sup.2]                         -6.85(2.72) ***
[LNPCM.sub.t-1]                    0.41(0.095) ***
[LNPCM.sub.t-2]                    0.304(0.09) ***
MS * MAM                           2.91(1.86)
[MS.sup.2] * MAM                   -7.967(2.868) ***
MAM                                1.22(0.062) ***
LogLikelihood                      -6063.90
Test [X.sup.2]
All variables                      [X.sup.2] (7)=1164.20 ***
MS, M[S.sup.2]                     [X.sup.2] (2)=49.21 ***
MS * MAM, [MS.sup.2] * MAM         [X.sup.2] (2)=9.40 ***
MS * MAM, [MS.sup.2] * MAM, MAM    [X.sup.2] (3)=471.96 ***
Observations                       14379

Source: Own tabulation from 2003 and 2005 PIA and PINTEC surveys
***, **, * means 1%,5% and 10% significance level, respectively
Note: DR&D is R&D dummy variable (1 if firm spent on R&D, 0 on
the contrary), MS is market share, [MS.sup.2] is market share
LNPCM.sub.t-1], [LNPCM.sub.t-2] is price cost margin log lag 1 and 2.
MAM is a mix of appropriability mechanisms dummy variable, which
includes advertisement (it is one of a firm used one or more
appropriability mechanism, inclusive advertisement, and zero on the
contrary). MS * MAM is market share- mix of appropriability indicator
interaction, [MS.sup.2] * MAM is market share squared- mix of
appropriability indicator interaction.
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