Abstract
This paper analyses the role that quality standards and innovation play on trade volume, by using a gravity model. The role of innovative activity and quality standards in enhancing trade performance is widely accepted in the literature. However, in this paper, we argue that the net effect of quality standards on trade is affected by the exporter’s ability to innovate and comply with these requirements. In particular, by using a sample of 60 exporting countries and 57 importing countries, for a wide range of 26 manufacturing industries over the period 1995–2000, we show that the most innovative industries are more likely to enhance the overall quality of exports, and then gain a competitive advantage. We also find that this effect depends on the level of technology intensity at industry-level and on the level of economic development of exporting country.
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Notes
The theoretical literature emphasizes innovation’s ability in creating new products or expanding the range of products that countries could produce and export (Grossman and Helpman 1989). Studies focusing on heterogeneous firms’ innovation data to explain their export activities find that in addition to a direct effect of innovation on exports, product innovation, through its effect on firm productivity, increases the likelihood of the firm entering the export market. (Bernard and Jensen 2004; Bleaney and Wakelin 2002; Cassiman and Golovko 2011; Becker and Egger 2013). Recently Chen (2013) finds that the extensive margin plays a more important role in science-based sectors, such as chemical and electronic equipment, and the estimates illustrate the impact of innovation on exports is decreasing with countries income levels.
With regard to the destination markets, several studies find that standards limit market access, particularly for developing countries (DCs) and Least Developed Countries (LDCs) towards developed countries, and their impact can be more restrictive than tariffs.
Perinorm is a database containing information on the standards published by the main national and international standards authorities.
Three different proxies for NTMs are used. The first indicator of NTMs is a dummy variable equal to one if the importing country notifies at least one barrier at the HS6 digit level; the second indicator is a frequency index, and finally a third dial is an ad-valorem equivalent.
On a partially related ground, many studies find that the negative impact of sanitary and phytosanitary measures (SPS) and technical barriers to trade are stronger when exports to the EU market are considered. Other studies show how stringency measures, such as the MRLs of pesticides and contaminants, negatively affect bilateral trade flows (Otsuki et al. 2001; Xiong and Beghin 2012; Disdier and Marette 2010). While others point out that similar regulations between trading partners may promote bilateral trade flows (Drogué and Demaria 2012; Vigani et al. 2011).
Since the bilateral trade flows are collected from multiple countries, heteroskedasticity may be a challenge especially in the common practice of logarithmic transformation. As Santos Silva and Tenreyro (2006) showed, if the true gravity equation is in its multiplicative form and heteroskedasticity is present, estimates from the log-linearized gravity equation can be biased. This specification of the gravity model solves three kind of problems. Indeed, thanks to its multiplicative form, the PPML specification provides a natural way to deal with zero trade flows. In addition, the estimations of the gravity model by PPML are consistent in the presence of heterosckedasticity and are reasonably efficient, especially in large samples. Finally, the objective function is log-linear instead of log-log. This imply that the dependent variable do not have to be transformed logarithmically.
One solution to this problem would be to instrument innovation, but unfortunately finding credible instruments at disaggregated level is not feasible.
Note that all countries do not produce all available goods, nor do they all have an effective demand for all available goods. Accordingly, the final dataset excludes products that are never traded.
As a matter of fact, data on NTMs can also be obtained from United Nation’s Conference on Trade and Development (UNCTAD), from World Trade Organization (WTO) and from the Trade Analysis and Information System (TRAINS) database.
As the literature suggests, international standards are less restrictive than domestic or regional ones. However, standards differ depending on products type with respect to the quality, safety as well as production and packaging. Even if the frequency index does not include the severity or the stringency of a specific measure, it allows us to know information about the number of product categories subject to NTMs. In this context, we make the assumption that the higher the number of requirements the higher the quality of products. This is because if the regulation is large then standards are promoting important public policy objectives, such us consumer safety and protection of the domestic market.
Data are available at http://www.nber.org/patents/. Broadly speaking, the dataset comprises detailed information on almost 3 million US patents granted between January 1963 and December 1999, all citations made to these patents between 1975 and 1999 (over 16 million), and a reasonably broad match of patents to Compustat (the data set of all firms traded in the US stock market) (Hall et al. 2001).
Since the original data on patents are classified according to the US Patent Classification, we combined them with other information adopting the correspondence scheme between the US Patent Classification and the International Patent Classification and between the latter and the ISIC Rev. 3 provided by Johnson (2002). Finally, concordances between ISIC Rev. 3 and ISIC Rev. 2 are applied.
Since in our sample the 25 % of the distribution of quality standards includes values equal to zero, we re-estimate our model on the sample of positive quality measures and the results, available on request, remain unchanged.
Both innovation and quality standards can be endogenous since exports can affect the incentive to apply for patents (Chen 2013) and bring about high number of standards. To deal with the causality problems of both quality and innovation, we estimate our model by using the GMM-system estimator. The equation is estimated using, as GMM-type instruments, lagged values of the dependent variable (X), of Y, E, dated t-2 and earlier and lags t-3 and earlier of Patent, Standard and Patent*Standard. As IV-type instruments, we adopt the lagged level of Tariff and country, time and industry dummies. Even though we obtain a negative coefficient of the interaction term, the total impacts of both Patent and Standard are positive. Results are reported in the Appendix Table 5. The Hansen test of overidentifying restrictions reveals that lagged patent counts and lagged quality standards are not exogenous instruments to current export flow. This could explain the negative sign of the interaction term.
A further investigation analyses differences in trade between countries according to the different levels of income. Looking at trade between middle-income countries, we find that the innovation has not an effect on trade and the quality standards act as compliance costs. When the trade is between similar countries any additional requirements on quality is a barrier to trade. Completely different is the scenario when we look at trade between middle-income and high-income countries. In this case the quality standards have a positive impact and they work as a quality/innovation incentive. Products from middle-income countries reach markets of developed economies in which consumers demand higher quality products. These results are available on request.
References
Acs Z, Audretsch D (1989) Patents as a measure of innovative activity. Kyklos 42:171–180
Acs Z, Anselin L, Varga A (2002) Patents and innovation counts as measures of regional production of new knowledge. Res Policy 31:1069–1085
Anderson JE, van Wincoop E (2003) Gravity with gravitas: a solution to the border puzzle. Am Econ Rev 93:170–192
Anderson JE, Yotov YV (2010) The changing incidence of geography. Am Econ Rev 100(5):2157–2186
Anderson JE, Yotov V (2012) Gold Standard Gravity. NBER Working Papers 17835, National Bureau of Economic Research, Inc.
Anderton B (1999a) UK trade performance and the role of product quality, innovation and hysteresis: some preliminary results. Scottish Journal of Political Economy 46:570–595
Anderton B (1999b) Innovation, product quality, variety, and trade performance: an empirical analysis of Germany and the UK. Oxf Econ Pap 51:152–167
Becker SO, Egger P (2013) Endogenous product versus process innovation and a firm's propensity to export. Empir Econ 44(1):329–354
Bernard AB, Jensen JB (2004) Why some firms export. Rev Econ Stat 86(2):561–569
Bleaney M, Wakelin K (2002) Efficiency, innovation and exports. Oxf Bull Econ Stat 64(1):3–15
Blind K (2001) The impacts of innovations and standards on trade of measurement and testing products: empirical results of Switzerland’s bilateral trade flows with Germany, France and the UK. Inf Econ Policy 13(4):439–460
Blind K, Jungmittag A (2005) Trade and the impact of innovations and standards: the case of Germany and the UK. Appl Econ 37(12):1385–1398
Bottazzi L, Peri G (2003) Innovation and spillovers in regions: evidence from European patent data. Eur Econ Rev 47:687–710
Bureau JC, Bernard F, Gallezot J, Gozlan E (2004) The measurement of protection on the value added of processed food products in the EU, the US, Japan and South Africa. A preliminary assessment of its impact on exports of African products. The World Bank, Final Report, July 26
Buxton T, Mayes D, Murfin A (1991) UK trade performance and R&D. Econ Innov New Technol 1:243–256
Cassiman B, Golovko E (2011) Innovation and internationalization through exports. J Int Bus Stud 42(1):56–75
Chen WC (2013) The extensive and intensive margins of exports: the role of innovation. World Econ 36(5):607–635
Chen MX, Mattoo A (2004) Regionalism in Standards: Good or Bad for Trade, Policy Research Working Papers, No. 3458, World Bank, Washington, DC
Cipollina M, Giovannetti G, Pietrovito F, Pozzolo AF (2012) FDI and growth: what cross-country industry data say. World Econ 35(11):1599–1629
Coe D, Helpman E (1995) International R&D spillovers. Eur Econ Rev 39:859–887
Coe D, Helpman E, Hoffmaister AW (2009) International R&D spillovers and institutions. Eur Econ Rev 53:723–741
de Frahan HB, Vancauteren M (2006) Harmonization of food regulations and trade in the single market: evidence from disaggregated data. Eur Rev Agric Econ 33(3):337–360
Desta MG (2008) EU sanitary standards and sub-Saharan African agricultural exports: a case study of the livestock industry in East Africa. The Law and Development Review 1(1):6
Disdier A-C, Marette S (2010) The combination of gravity and welfare approaches for evaluating non-tariff measures. Am J Agric Econ 92(3):713–726
Disdier AC, Fontagné L, Mimouni M (2008) The impact of regulations on agricultural trade: evidence from the SPS and TBT agreements. Am J Agric Econ 90(2):336–350
Drogué S, Demaria F (2012) Pesticide residue and trade, the apple of discord. Food Policy 37(6):641–649
Eaton J, Kortum S (2001) Technology, trade, and growth: a unified framework. Eur Econ Rev 45(4–6):742–755
Eaton J, Kortum S (2002) Technology, geography, and trade. Econometrica 70(5):1741–1779
Edwards K, Gordon T (1984) Characterization of innovations introduced on the US market in 1982. Report prepared for the US Small Business Administration. The Futures Group. Department of commerce, Washington: NTIS.
Engelbrecht HJ (1997) International R&D spillovers, human capital and productivity in OECD economies: an empirical investigation. Eur Econ Rev 41(8):1479–1488
Feenstra RC (2002) Border effects and the gravity equation in international economics: theory and evidence. Scottish Journal of Political Economy 49(5):491–506
Fontagné L, Mimouni M, Pasteels JM (2005) Estimating the impact of environmental SPS and TBT on international trade. Int Trade J 22:7–37
Garcia Pires AJ (2014) Beyond trade costs: firms’ endogenous access to international markets. Journal of Industry, Competition and Trade, Springer, vol 14(2):229–257
Greenhalgh C (1990) Innovation and trade performance in the United Kingdom. Econ J 100:105–118
Greenhalgh C, Taylor P,Wilson R (1994) Innovation and Export Volumes and Prices-A Disaggregated Study. Oxford Economic Papers, pp. 102–135
Griliches Z (1998) Patent statistics as economic indicators: a survey. In R&D and productivity: the econometric evidence, pp. 287–343. University of Chicago Press
Grossman GM, Helpman E (1989) Product development and international trade. J Polit Econ 97(6):1261–1283
Grossman GM, Helpman E (1991a) Quality ladders and product cycles. Q J Econ 106(2):557–586
Grossman GM, Helpman E (1991b) Quality ladders in the theory of growth. Rev Econ Stud 58(1):43–61
Hall BH, Jaffe AB, Trajtenberg M (2001) The NBER patent citation data file: Lessons, insights and methodological tools. NBER Working Papers 8498, National Bureau of Economic Research.
Iimi A (2007) Infrastructure and trade preferences for the livestock sector: empirical evidence from the beef industry in Africa. World Bank Policy Research WP 4201
Johnson DKN (2002) The OECD technology concordance (OTC): patents by industry of manufacture and industry of use OECD Science, Technology and Industry. WP n. 2002/5. http://wwwoecd-ilibraryorg/science-and-technology/the-oecd-technology-concordance-otc_521138670407
Medvedev D (2010) Preferential trade agreements and their role in world trade. Rev World Econ 146(2):199–222
Moenius J (2004) Information Versus Product Adaptation: The Role of Standards in Trade, Available at SSRN: http://ssrn.com/abstract=608022 or http://dx.doi.org/10.2139/ssrn.608022
Moenius J (2006) The Good, the Bad and the Ambiguous: Standards and Trade in Agricultural Products, IATRC Summer Symposium, May 28–30, Bonn
Okumura Y (2015) Free trade networks on non-tariff barriers. Journal of Industry, Competition and Trade 15(3):223–238
Otsuki T, Wilson JS, Sewadeh M (2001) What price precaution? European harmonisation of aflatoxin regulations and African groundnut exports. Eur Rev Agric Econ 28(3):263–284
Pavitt K, Robson M, Townsend J (1987) The size distribution of innovating firms in the UK: 1945–1983. J Ind Econ:297–316
Pöyhönen P (1963) A tentative model for the volume of trade between countries, Weltwirtschaftliches Archiv, pp. 93–99
Santos Silva J, Tenreyro S (2006) The log of gravity. Rev Econ Stat 88:641–658
Siggel E (2006) International competitiveness and comparative advantage: a survey and a proposal for measurement. Journal of Industry, Competition and Trade, Springer 6(2):137–159
Swann P, Temple P, Shurmer M (1996) Standards and trade performance: the UK experience. Econ J 106:1297–1313
Tinbergen J (1962) Shaping the world economy. Suggestions for an international economic policy. The Twentieth Century Fund, New York
Vigani M, Raimondi V, Opler V (2011) International trade and Endegenous standards: the case of GMO regulations. World Trade Review 11(3):415–437
Wakelin K (1998) The role of innovation in bilateral OECD trade performance. Appl Econ 30(10):1335–1346
Xiong B, Beghin JC (2012) Does European aflatoxin regulation hurt groundnut exporters from Africa? Eur Rev Agric Econ 39(4):589–609
Acknowledgments
We would like to thank Giovanni Anania, Alberto Franco Pozzolo and Luca Salvatici for helpful comments on an earlier draft of the article. This article has been co-funded by the Region Calabria (Programma Operativo Regione Calabria FSE 2007/2013) and by INRA UMR MOISA (Institut national de la recherche agronomique - Unité Mixte de Recherche - Marchés, Organisations, Institutions et Stratégies d’Acteurs). The views expressed in this article are the sole responsibility of the authors and do not necessarily reflect those of the INRA UMR MOISA or the Region Calabria.
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Appendix
Appendix
Table 5 presents descriptive statistics of our variables of interest. They are calculated on the whole sample, after excluding influential observations, i.e. observations with a value of trade higher that the 95th percentile of the world distribution. Concerning the dependent variable, i.e. exports, it shows an average value of more than 35 million dollars and a high variability, with values ranging between 0 and 526 million dollars. Total production reflects the economic development of exporter countries, with minimum value of 638,000 dollars for Panama (in 1996), and the maximum value of more than 639 billion dollars for USA (in 1999). Moreover, consumption show minimum values of 1163 thousand dollars for Cameroon (in 1997) and the highest value of 698 billion dollars for USA (in 1999).
Among bilateral characteristics, Distance shows an average of more than 7 thousand kilometres, with values ranging between 80 and more than 19 thousand kilometres. Tariffs show a high variability, with values ranging between 0 and 268 % and an average level of about 5 %.
Moreover, the number of patents, which reflects the technological development, is also highly variable in our sample, with values ranging between 0 (for manufacture of fabricated metal products in China) and 924 (for manufacture of food, beverages and tobacco in USA) and an average equal to 4. The frequency index of restrictions on quality ranges between 0 and 1 and shows and average value of 0.11.
Table 6 reports simple correlations among the variables used in the empirical model. As expected, exports are positively correlated with production, consumption common language and innovation. Negative correlations are reported between exports distance, tariff barriers, and, surprisingly, quality standards. Moreover, a positive and significant correlation (0.24) is reported between tariff and non-tariff measures. Even though summary statistics and bilateral correlations are suggestive, they do not control for potentially confounding factors. For this reason, in what follows we perform a more refined econometric analysis.
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Cipollina, M., Demaria, F. & Pietrovito, F. Determinants of Trade: the Role of Innovation in Presence of Quality Standards. J Ind Compet Trade 16, 455–475 (2016). https://doi.org/10.1007/s10842-016-0234-z
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DOI: https://doi.org/10.1007/s10842-016-0234-z