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Intellectual property rights, distance to the frontier, and R&D: evidence from microdata

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Abstract

Using firm-level data for 28 transition countries in Eastern Europe and Central Asia over the 2002–2009 period, this paper analyzes whether differences in the functioning of intellectual property rights (IPRs) systems—measured along various dimensions, including de facto enforcement and de jure patent and copyright protection—affect a firm’s propensity to engage in R&D activities. We estimate the likelihood of engaging in R&D as a function of a firm’s distance from the relevant technological frontier and of the country’s IPRs system. In line with previous literature, we find that (i) firms closer to the technological frontier are more likely to engage in formal R&D activities and (ii) stronger IPRs systems, because they protect returns from R&D activities from imitation, are more effective in promoting investment in R&D. Moreover, when the strength of an IPRs system interacts with the distance to the technological frontier, its effect is no longer significant, ceteris paribus. This is the most striking result of our study. When we examine the semi-elasticity of the strength of IPRs with respect to a firm’s distance from the technological frontier, a weak yet positive impact on the firm’s likelihood to engage in R&D is observed for very inefficient ones, whereas this becomes negative and weakly significant when firms are on the technological frontier.

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Notes

  1. For example, the implementation of the national treatment principle prescribed by international agreements, entailing equally strong protection for both domestic and foreign innovations, may be incomplete or even deliberately pursue the strategy of favoring the adoption of technology from abroad (Lorenczik and Newiak 2012). From such a perspective, the existence of a non-linear relationship between the strength of IPRs protection and innovation suggests that the enforcement of the national treatment principle may negatively impact the innovation activities of domestic firms (Lorenczik and Newiak 2012).

  2. I.e., through reverse engineering or the adoption of external technologies via new equipment.

  3. The sampling methodology follows the rules of the World Bank’s Enterprise Surveys. Details on the construction of the survey can be found on the homepage of the EBRD under “http://www.ebrd.com/pages/research/economics/data/beeps.shtml”. Lee and Weng (2013) provide a short yet exhaustive description of the survey process.

  4. Labor productivity in the sampled countries is expressed in real terms and has been transformed into US dollars from local currency units. We first deflated the sales figures via the country-year-specific GDP deflators. We then used the average of the monthly averages of the exchange rates in the focal year to transform the real values into US terms.

  5. Because industry-specific deflators are not available for most countries in this study, we relied on the broader GDP deflator. Exchange rates are for the year of the interview and calculated as the average of monthly averages. The only exception is Uzbekistan, for which information about exchange rates was not reported. Thus, this information was manually extracted from specialized websites and calculated as the average of the last days of all the months in the focal year.

  6. The full description of the components of the intellectual section of the Property Rights Index and their sources are available on the website of the parent organization, Property Rights Alliance: http://www.internationalpropertyrightsindex.org/methodology.

  7. i.e., Ginarte and Park (1997) and Park (2008).

  8. The large number of questions contained in the BEEPS naturally leads to high non-response rates across variables. Furthermore, information from the CMS provides limited sectoral coverage. Hence, we restrict our analysis to those firms in the manufacturing sector for which information about the key variables of the study is available across all sources (R&D, distance to the technological frontier, importance of different appropriation mechanisms). Missing observations for control variables have been substituted with arbitrary values calculated by using interpolation to find intermediate points and controlled with a dummy for missing observations in order to include as many observations as possible.

  9. In fact, according to the data released by the Statistical Office of the Republic of Slovenia (http://www.stat.si/eng/novica_prikazi.aspx?id=3521), in 2009, the total gross domestic expenditure on R&D (GERD) accounted for 1.86 % of Slovenian GDP. Noticeably, the highest share of GERD was contributed by companies, which provided 58 % of the total funding for R&D.

  10. The results do not change when we set the threshold at different values, such as 50, 80, or 100.

  11. To the purpose, we attempted an instrumental approach and extensively searched for instruments that were exogenous, not correlated with ε i , relevant, and strongly correlated with our measure of distance from the technological frontier. Among others, we used the mean of the distance values—excluding the focal firm—for each country, year, and industry; the number of firms was considered in the survey for each country, year, and industry. No instrument satisfied the exogeneity requirements. This shows that distance to the frontier is likely influenced by R&D, along with a consequent simultaneity problem due to the error term affecting both the response and the explanatory variable. Thus, we take the results presented below as partial correlations, and we will interpret them accordingly.

  12. The average share of products for which patents were considered effective across sectors is 31; the median is 33.

  13. In general, when foreign investors have 51 % or more of the shares in the focal company, firms are found to be less likely to invest in R&D (negative and slightly significant coefficient of the FOREIGN variable).

  14. Small firms controlled by foreign investors are generally less likely to invest in R&D (negative and significant coefficient of the FOREIGN variable).

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Authors and Affiliations

  1. Faculty of Economic and Applied Economic Sciences, KU Leuven, Naamsestraat, 69, 3000, Leuven, Belgium

    Antonio Della Malva

  2. Department of Economics, University of Bologna, Piazza Scaravilli, 2, 40126, Bologna, Italy

    Enrico Santarelli

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  1. Antonio Della Malva
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Correspondence to Enrico Santarelli.

Additional information

Preliminary versions of this paper have been presented at the 5th ZEW/MaCCI Conference on the Economics of Innovation and Patenting (Mannheim, June 3–4, 2013), at the 9th Annual Conference of the Italian Association of Law and Economics (Lugano December 12–13, 2013), and at a seminar held at Depocen—development and policies research center (Hanoi, 20 January 2014). We thank Emanuela Carbonara for her many valuable suggestions; Luigi A. Franzoni, Marit Klemetsen, Mikael Pellens, Hien Thu Tran, the Editor-in-chief and two reviewers of this journal for their comments on previous versions of the paper.

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Malva, A.D., Santarelli, E. Intellectual property rights, distance to the frontier, and R&D: evidence from microdata. Eurasian Bus Rev 6, 1–24 (2016). https://doi.org/10.1007/s40821-015-0022-4

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