Competitive Conditions Affecting U.S. Exports of Medical Technology to Key Emerging Markets
Peter Herman
Jeff Horowitz
Mihir Torsekar
Working Paper 2018–08–A
500 E Street SW
Washington, DC 20436
August 2018

Office of Economics working papers are the result of ongoing professional research of USITC Staff and are solely meant to represent the opinions and professional research of individual authors. These papers are not meant to represent in any way the views of the U.S. International Trade Commission or any of its individual Commissioners. Working papers are circulated to promote the active exchange of ideas between USITC Staff and recognized experts outside the USITC and to promote professional development of Office Staff by encouraging outside professional critique of staff research.

Competitive Conditions Affecting U.S. Exports of Medical Technology to Key Emerging Markets
Peter Herman, Jeff Horowitz, and Mihir Torsekar
Office of Economics Working Paper 2018–08–A


The United States is the world’s largest supplier of medical technology (medtech). At the same time, growth in key emerging medtech markets—especially China, India, and Brazil—represent significant export opportunities for U.S. manufactures to further bolster their competitiveness. Yet, import restrictions arising from onerous regulatory procedures in these countries limit U.S. exports to these markets, particularly by extending the time to market for these goods to gain approval for sale. Using a gravity model approach, we estimate ad valorem equivalents (AVEs) for non-tariff measures (NTMs) in 167 countries and find that China, India, and Brazil all rank in the bottom half in terms of import competitiveness. Further, we run a second stage regression to identify specific factors that depress advanced medtech exports. Our results show that the estimated competitiveness of each country is tied to regulatory measures rather than demand factors. In particular, lengthy time-to-market and regulatory complexity significantly reduce a country’s import competitiveness. These findings suggest that the harmonization of China’s, India’s, and Brazil’s medtech standards to internationally accepted best practices would likely translate into greater U.S. exports to these markets. This paper is the first to quantify the impact of regulatory procedures on the import competitiveness of various global medtech markets.

Peter Herman
Office of Economics
U.S. International Trade Commission
Jeff Horowitz
Office of Industries
U.S. International Trade Commission
Mihir Torsekar (corresponding author)
Office of Industries
U.S. International Trade Commission

1 Introduction

In recent years, the $400 billion global market for medical technology (medtech) has expanded rapidly as countries increasingly demand access to quality healthcare and the tools that provide it (Evaluate Medtech 2017). The United States, in particular, has benefitted from this market growth as it is the world’s leading provider of medtech products, representing close to one-quarter of global exports in 2016 (Comtrade, 2018). However, with growth in established markets (e.g. Germany and Japan) likely to remain relatively stable in the near term, emerging markets—such as China, India, and Brazil—may suggest opportunities for the United States to maintain its competitive trade position. In addition to boasting large populations, growing GDPs, and rising GDP per capita, each of these three countries have sizeable disease burdens and relatively low per capita spending on medical devices (medical device density) (The World Bank, 2018). Yet, despite these factors, our analysis finds that China, India, and Brazil remain relatively small importers of medtech.

In order to better understand medtech trade and the factors that limit it, we estimate gravity trade models using bilateral trade data for each of a collection of medtech products. The results of the gravity models are used to rank countries based on their import competitiveness. Import competitiveness is a measure that reflects the value of imported medtech relative to a country’s economic size; a country that imports large values of medtech given their GDP is considered highly competitive while a country that imports relatively little is considered uncompetitive.1 To more concretely measure import competitiveness, we also calculate estimated ad valorem equivalent (AVE) trade costs that explain differences in competitiveness across 167 countries.2 Using this methodology, we find that China (ranked 126), India (ranked 125), and Brazil (ranked 92) rank relatively low in terms of import competitiveness compared to the rest of the world, suggesting that there is considerable export potential for U.S. firms if the source of this lack of competitiveness can be addressed.

Next, we conduct a second regression using data that reflects regulatory requirements and medtech demand in order to identify the factors that influence import competitiveness. These estimates indicate that long and complicated approval processes significantly reduce import competitiveness, while key demand factors (per capita healthcare spending and medical device expenditures) have no effect. As the world’s most innovative medtech producer, the United States is especially disadvantaged by regulatory delays (Torsekar, 2014; USITC, 2007). This concern is aggravated by the relatively short product lifecycle (18-24 months) of the most advanced medtech for which the United States is especially competitive in manufacturing. Therefore, our results provide strong evidence that the United States will stand to benefit significantly from the harmonization of policy measures in the Chinese, Indian, and Brazilian medtech markets to international best practices.

This work adds to the literature attempting to measure the impacts of trade restrictiveness measures. Kee, Nicita, and Olarreaga (2009) builds trade restrictiveness indices for 78 developed and developing countries. They estimate the trade restrictiveness indices (TRI) for countries by estimating AVEs of NTMs impact on imports, and then using that to observe the difference between a country’s overall restrictiveness and its tariff rates. Moreover, Kee, Nicita, and Olarreaga (2008) use Feenstra’s (1995) simplified trade restrictiveness index (TRI) at the country level rather than at the product level. Their results support the conclusion that poor countries have more restrictive trade policies and face higher export barriers. However, the quantitative analysis that has been done on the medtech sector specifically is quite limited. Sunesen, Francois, and Thelle (2009) find that medical device exports from the EU to Japan could increase by as much as 84 percent if the level of NTMs in Japan was comparable to that of the EU, but do not evaluate different types of NTMs. Additionally, a USITC (2007) study examining the competitive conditions affecting medtech trade identified “time to market” as a principal concern with respect to its effect on sales, but provided no empirical verification for this. To the best of our knowledge, our paper represents one of the first studies focusing entirely on quantifying policy barriers in medtech trade across multiple countries.

The paper proceeds as follows. Section 2 defines medtech and describes how it is regulated. Section 3 presents an overview of the U.S. industry, as well as the current markets and regulatory environment in the key emerging markets of China, India, and Brazil. Section 4 describes the empirical methodologies used to measure import competitiveness and restrictiveness and presents the estimated results. Section 5 concludes.

2 Medical Technology and Regulations

Medical technologies refer to the various implements, machines, appliances, and instruments that facilitate in the diagnosis, treatment, or alleviation of disease (WHO 2003). The products included in the medtech industry range in complexity from relatively unsophisticated goods, such as bandages and other hospital supplies, to high-tech capital goods, such as diagnostic equipment. Although there are several ways to classify medtech, recent research by Torsekar (2018a, 2018b) has applied a similar framework developed by Bamber and Gereffi (2013), which identifies four major product groupings, ranging from least to most sophisticated: (1) disposables (bandages, surgical gloves, and plastic syringes); (2) surgical and medical instruments (devices used in surgeries and cosmetic procedures); (3) therapeutics (includes implantable devices like hearing aids and prosthetics and non-implantable devices such as ventilators and infusion pumps); and (4) diagnostic equipment (capital equipment that is technologically complex). For the purposes of this paper, we emphasize trade in therapeutics and diagnostics because the majority of regulatory procedures apply to these devices. A full list of products included in the study can be found in table 4 in the appendix.

2.1 Regulating Medtech

Regulatory practices are critical determinants of overall trade competitiveness for a given country, influencing market access for foreign producers and guiding pricing decisions of products within these markets. In the global medtech industry, nearly all major markets apply a risk-based classification system to regulate these goods, similar to the recommendations of the International Medical Device Regulators Forum (IMDRF), a voluntary international association aimed at harmonizing international medical device standards. The IMDRF builds upon similar efforts made by the The Global Harmonization Task Force (GHTF) which, prior to being disbanded in December 2012, recommended dividing medical devices into four categories based on the relative harm posed to patients; regulatory requirements are ideally supposed to increase in accordance with the device risk (figure 1).3

Figure 1: Conceptual illustration of the device class and corresponding regulatory requirements, as stipulated by the GHTF.
Illustration depicting that regulatory requirements increases with each subsequent device class.
Source: (GHTF, 2012, p. 11).

Despite the prevalence of risk-based classification standards for medtech and escalating regulatory requirements for higher-risk devices within most international markets, differences in the application of specific measures can restrict trade by imposing NTMs, thereby limiting or delaying market access to foreign manufacturers (Johnson, 2008, p. 1). According to UNCTAD (2012), there are 16 recognized NTMs, of which technical barriers to trade (TBTs) are most germane to the global medtech market. TBTs typically refer to three types of measures (UNCTAD 2012; WTO 1995):

While the 1995 WTO Agreement on TBTs (TBT Agreement) permits countries to implement their own regulations, standards, and conformity assessment procedures to fulfill legitimate regulatory concerns, countries are encouraged to accept other member countries conformity assessment procedures. With regard to medtech production, class C-D devices are subject to the highest regulatory scrutiny; manufacturers are required to submit to on-site audits of production facilities, submit documentation detailing the product design, provide data from product testing, and maintain a quality management system (QMS) (GHTF, 2012, p. 8-17).4 However, these procedures can run afoul of the TBT Agreement when they are deemed discriminatory, conferring an advantage to domestic producers at the expense of foreign manufacturers. Further, conformity assessment procedures requiring duplicative testing or product certifications and technical regulations imposing onerous labelling standards that require unnecessary information beyond the basics of what is needed to use the product are examples of likely TBT violations (UNCTAD, 2012).

When signatories of the TBT Agreement consider updating their regulations in ways that may significantly impact trade or diverge from international standards, they must notify the TBT committee; these notifications can serve as a proxy for understanding a country’s overall regulatory market (Okun-Kozlowicki, 2016). During January 2013–August 2018, China and Brazil ranked first and third (behind South Korea), respectively, as having the highest number of medical device notifications submitted to the TBT Committee (figure 2); India did not have any notifications during this time. It should be noted that while these notifications don’t necessarily connote TBT violations, they can suggest additional trade costs and possible delays in securing approval for sale, arising from the demands of adapting to changing regulations upon implementation. Many of the provisions that Brazil and China raised during this time ranged from labeling requirements, to inspection and auditing standards. An additional caveat is that countries with relatively immature regulatory systems who are seeking to adopt international standards will notify the TBT Committee to confirm that they are following best practices. Encouragingly, industry representatives report that this is more often than not, the case with Brazil and China’s notifications to the Committee.5

Figure 2: Number of Medical Device TBT Notifications for Selected Countries and the Rest of the World (ROW), January 2013-August 2018.
A bar chart depicting the number of TBT notifications in the medical device industry for Brazil, China, the EU, U.S., Japan, Canada, Korea, and the Rest of the World. Brazil and China led the world in these notifications at 16 and 30, respectively.
Source: TBT Information Management System (2018, accessed August 11, 2018

3 Overview of U.S. Industry and Key Emerging Markets

The U.S. medical device industry, which is valued at more than $153 billion in 2016, is the world’s largest (EY, 2017). Moreover, seven of the world’s ten largest medical device original equipment manufacturers (OEMs), by revenue, are headquartered in the United States (table 1). Although large firms command the greatest domestic market share, more than 80 percent of the industry’s 1,500 firms are small and medium-sized enterprises (SMEs) that employ less than 50 people (Carusi, 2014). Nonetheless, it is typically the larger OEMs that commercialize most medical devices due, in large part, to their financial resources. Despite producing devices across 90 distinct categories of products, U.S. firms specialize in high-value-added technologies requiring a highly skilled workforce of engineers and technicians. The U.S. medical device industry accounts for more than two million jobs (both indirectly and directly) throughout the country, paying wages that exceed most manufacturing jobs by 30 percent and 9,800 manufacturing facilities both in the United States and around the world (AdvaMed, 2017).

Table 1: Top 15 global medical device manufacturers in 2017 by revenue, headquarters, and 2015 market share.
Company Headquartered
Revenue ($ bn)
Global Market Share (%)
Medtronic Ireland 28.8 8
Johnson & Johnson United States 25.1 6
Siemens Healthineers Germany 15.2 3
Becton Dickinson United States 12.5 3
Cardinal Health United States 12.4 3
Phillips HealthTech The Netherlands 12.4 3
Stryker United States 11.3 3
Baxter United States 10.2 2
Abbot Laboratories United States 10.1 2
Boston Scientific United States 8.4 2
Danaher United States 7.8 2
Zimmer Biomet United States 7.7 2
Essilor France 7.5 2
B.Braun Germany 6.8 2
Top 15 totals 176.2 43

Source: Fenske et al. (2017) and Snyder (2017).
Note: Market share data presented for 2015, the most recent year for which these data were available.

The competitiveness of the U.S. advanced medtech industry is also reflected in their status as the world’s largest exporter of these goods (figure 3). U.S. medical device OEMs earn between 40 and 50 percent of their revenues outside the United States, which reflect a combination of exports and activities by foreign-based subsidiaries (SP, 2014). Export decisions are largely influenced by the ease of foreign market entry. This is because, given the relatively short lifecycle of these technologies (18-24 months), U.S. firms may forgo significant potential earnings if a device is undergoing a lengthy review in a foreign country (USITC 2007). To that end, U.S. manufacturers have commonly generated roughly 30 percent of their revenues from the European Union (EU)—led by Germany—which have the lowest reported times to market of any of the world’s major medical device markets (Emergo, 2017a).6 In addition, a principal advantage of maintaining a presence in a variety of international markets is the ability for firms to mitigate the effects of currency swings by focusing on markets that benefit from the current value of the U.S. dollar at a particular moment in time;7 in recent years, an estimated 40 percent of revenues garnered by the top 10 U.S. medical device OEMs stemmed from beneficial foreign exchange rates (EY, 2012).

Figure 3: The world's largest exporting countries of advanced medtech, 2016 (%)
Pie chart showing that the United States represented 23 percent of total global medtech exports in 2016.
Source: Comtrade (2018, accessed June 18, 2018).

Alongside Germany, Japan has also served as a leading destination for U.S. medtech. However, these established medtech markets are relatively mature,8 which implies relatively stable market growth. In contrast, the rapid expansion of key emerging medtech markets, led by China, India, and Brazil, may suggest substantial opportunities for U.S. manufacturers (Francis et al.,. 2011; Agarwal et al.,. 2016). Growth in these three countries reflects a combination of demographics (especially ageing populations in China), highly urbanized populations, and the growth and prevalence of non-communicable or lifestyle-related afflictions. At the same time, these three medtech markets remain chronically underserved. For example, medical device density for China, India, and Brazil each ranked in the bottom quartile according to a 2013 study by CHPI; out of the 67 countries studied, the three countries ranked 63rd, 58th, and 50th respectively.

The United States has been the largest supplier of medtech to China, India, and Brazil for the past decade. More specifically, the United States has represented more than one-quarter of each of these countries’ medtech imports during this time (Global Trade Atlas, 2018).9 However, our analysis (which will be discussed in section 4) finds that these key markets rank low in import competitiveness, especially when compared to established medtech markets (as depicted in table 2). In particular, each of these countries maintains regulatory structures that are associated with extensive times to market for high-risk devices. The regulatory obstacles mostly fall under the purview of TBTs (especially conformity assessment procedures and technical regulations), but also include other NTMs (such as price controls), as summarized below:

Table 2: Comparison of regulatory factors, demand factors, and overall barriers in advanced medtech for key emerging medtech markets and established medtech markets
Key emerging
medtech markets
medtech markets
China India Brazil Germany Japan
Regulatory Factors
Maximum time to market High High High Low Moderate
Regulatory Complexity High Moderate High Moderate Moderate
Regulatory Cost High Moderate High Moderate High
Demand Factors
Medical Device Density Low Low Low High High
Per capita Healthcare spending Low Low Moderate High High
Overall Barriers
Import Competitiveness Low Low Moderate High High

Source: Compiled by authors from Emergo (2017a).
Note: Ratings (low, moderate, high) for maximum time to market, import competitiveness, and medical device density were assigned based on quartile rankings of these respective data sets. Quartile rankings of 4 were ranked “low” for time to market and import restrictiveness and “low” for medical device density. The country data on regulatory complexity and cost was ranked from 1–5, with 1 being the lowest and 5 the highest. In these cases, we assigned a rating of “moderate” to countries assigned listed as a 3 or 4 and a “high” to countries with a ranking of 5. Per capita healthcare spending of below 5 percent of GDP were considered low, spending between 6–10 percent were considered moderate, and anything at or exceeding 11 percent was deemed high.

3.1 China

3.1.1 Market Overview

As of 2016, China’s medical device market was valued at $8.7 billion (Emergo, 2017b) and ranked second behind Japan as Asia’s largest market. In particular, China’s rapid rate of urbanization, aging population, and increasing incidence of lifestyle-related afflictions has created substantial demand for various categories of advanced medtech (Luo, et al. 2014). For example, unprecedented urbanization (Roxburgh, 2017) has heightened the need for diagnostic technologies, pacemakers, dialysis systems, and intravenous diagnostic technologies. This trend reflects the various public health risks that accompany city dwelling.10 For example, 1 in 10 adults (110 million people) in China are estimated to have been diagnosed with diabetes (WHO, 2016). Further, China’s elderly population (those aged 65 and above)—already one of the world’s largest—is generating growing demand for orthopedic devices within the country; China may become the world’s largest orthopedic device market within 10 years, according to recent projections (Liu, 2017). Elderly populations are generally the largest consumers of these devices, due to the degradation of the musculoskeletal system and loss of bone strength generally associated with aging.

At the same time, government policies have helped expand the growth of China’s healthcare market. In an attempt to redress the country’s historically inequitable healthcare system, China implemented healthcare market reforms in 2009. According to the EIU, these have since been associated with improvements in the country’s primary healthcare system, having achieved near-universal health insurance through the expansion of basic health insurance, limiting out-of-pocket expenses, and reforming public hospitals. Further, in late 2016, China unveiled the country’s first long-term strategic health plan (“Healthy China 2030”), which aims to build off of previous initiatives to extend life expectancy among its citizens, increase the number of doctors, and reduce out-of-pocket expenses (EIU 2018a). In accordance with these plans, China has steadily increased its healthcare spending, which reached a historic high of 6 percent of GDP in 2016 (EIU, 2017a). Nevertheless, China’s per capita total healthcare spending remains low compared to other leading markets, such as the United States (17 percent), Germany (11 percent), and Japan (10 percent), for example (EIU, 2018b,c).

3.1.2 Regulatory Overview

China is estimated to have the second longest time to market (behind the United States) and ranks among the world’s most complex and costly regulatory systems (Emergo, 2017a). China’s chief medical device regulatory agency, the China Food and Drug Administration (CFDA), is responsible for approving all devices for sale within the country. Much as in other markets, China requires foreign manufacturers to appoint an agent to liaise with the CFDA and an after-sales service representative after approval. The device registration process in China can be especially onerous and time consuming due to the requirement that foreign firms provide a file listing technical information, test reports, clinical data, and a document attesting to the quality of the device with all documentation provided in “simplified Chinese.” During this review, the CFDA reserves the right to perform audits of foreign manufacturers, which may entail an on-site review of production facilities (Emergo, 2016); these steps are often duplicative, as they have more than likely been performed in order to achieve market entry for sale in other countries (USTR 2016, 87).

Of particular concern to U.S. industry is China’s March 2014 revision of medical device regulations.11 These polices principally apply to conformity assessment measures and introduced two requirements on medical devices that have raised concerns from U.S. manufacturers. The first policy requires medtech exporters to be registered in their country before being eligible for registration in China. The second policy imposes new clinical trial requirements for the most advanced medical technologies. Both of these policies are believed to be associated with market delays and represent more stringent departures from previous policies (USTR, 2016, p. 88). For example, with regard to the new clinical trial requirements, China had previously permitted foreign firms that had obtained market clearance in other countries to sell in China without having to conduct multiple clinical trials (Luo et al., 2014). This practice was consistent with that applied in other leading markets, such as the EU, for example. In addition to adding to the overall approval times, this measure imposes high costs of between 1millionto1.5 million (Giger, 2017). These high costs would likely discourage small producers in the United States, who lack the financial resources of their larger counterparts.

At the same time, China has implemented policies aimed at bolstering the domestic manufacturing sector. As part of their “Made in China 2025” campaign, the country has prioritized the production of advanced medtech to meet their domestic requirements. By 2025, China has established a semi-official target of supplying 70 percent of their domestic market for these goods with local production (Wubbeke, 2016). In particular, their innovation policies appear to favor domestic production over foreign (EIU, 2017b; Agarwal, 2015). For example, Chinese companies have been the principal beneficiaries of the country’s expedited review process for the most innovative devices; 90 percent of the 117 approved devices under this procedure have been produced by Chinese firms as of 2017 (EIU, 2017b).

These policies are consistent with China’s pricing policies, which are believed to disadvantage the types of advanced medical technology commonly supplied by the United States. China’s provincial tendering process, which determines the price at which medtech is sold, is associated with high administrative requirements that translate into lengthy delays for foreign manufacturers. For example, advanced medtech manufacturers must provide detailed specifications of their products and often enter into lengthy negotiations with the government in order to justify the higher prices that these goods command; it can take years before a device is priced for sale in a particular province (Torsekar, 2014). At the same time, U.S. industry representatives have suggested that price controls are applied in the tendering process, with ceiling prices that discourage the adoption of foreign medtech (USTR, 2017, p. 57).

3.2 India

3.2.1 Market Overview

India’s medical device market is valued at roughly $5-6 billion12 and ranks as Asia’s fourth largest medical device market behind Japan, China, and South Korea (Emergo, 2017b). The market is largely being driven by rapid urbanization, the emergence of non-communicable diseases (e.g. cardiovascular disease and diabetes), and a growing middle class (Dey, 2017; SKP, 2017). Because domestic production is concentrated in disposables and other low-end segments, roughly three-quarters of its medical device market is supplied by imports, with the United States being the largest supplier (Torsekar, 2017). The highest imported categories of devices include therapeutics (especially hearing aids, pacemakers, and stents) and diagnostic equipment (SKP, 2017). Despite the large potential market opportunity, India’s healthcare system is chronically underfunded, spending less than five percent of its GDP on healthcare (EIU, 2018d).

3.2.2 Regulatory Overview

In contrast to all of the twenty foreign markets for which time to market data was available, India has been unique in its absence of a risk based classification structure. Instead, the country’s regulations have only extended to 22 types of devices, a process that created ambiguity with respect to classifying devices outside of these categories. Further, India has typically regulated medical devices as analogous to pharmaceuticals despite the notable differences between the two products, including the way that these products are designed, manufactured, and administered to patients, for example.

A report from the USITC from 2014 noted that the disparity between regulated and unregulated devices, along with the requirement to comply with standards more appropriate for pharmaceuticals than medical devices created substantial burdens on foreign manufacturers. For example, producers of unregulated devices could be compelled to provide various documentation and paperwork at any time even after a device has been placed in the market; each document required of these firms was estimated to cost $1,000 (USITC, 2014).

In addition, during 2014, India’s Central Drugs Standard Control Organization—a regulatory body that governs the imports of medical devices—implemented India-specific labeling requirements for exporters of medtech. These standards list 14 steps that must be placed on a medtech label, including the date and place of manufacture, the maximum retail price, and manufacturing license numbers, to name a few (Morulaa, n.d; USITC, 2014). These requirements exceed GHTF recommendations, which advise that country-specific labeling be “kept to a minimum” or removed entirely (GHTF, 2011).

In response to these challenges, the Ministry of Health and Family Welfare in India began implementing the Medical Devices Rule of 2017 on January 1, 2018. Encouragingly, the policy has established the country’s first risk-based classification system for all medical devices and distinguishes these goods from pharmaceuticals. At the same time, these measures eliminate onerous procedures, such as the requirement for foreign manufacturers to register medical devices intended for sale and the periodic renewal of licenses (SKP, 2017; IQVA, n.d.).

Yet, even as India has made advances in standardizing its regulatory regime with international practices, the country has also pursued policies aimed at reducing its reliance on foreign imports while bolstering its domestic industry. According to SKP (2017), the country decided in February of 2017 to impose price controls on coronary stents,13 reducing their prices by nearly 75 percent. In August of 2017, a similar policy on knee implants reduced prices by as much as 87 percent depending on the type of device. Both policies have faced strong objections from U.S. manufacturers. For example, leading U.S. producers including Abbot Vascular and Boston Scientific attempted to withdraw their products from the market as a result, despite prohibitions against such actions for 12 months from the date of the notification. Further, in March of 2018, India’s Department of Pharmaceuticals issued a public procurement order which includes local content requirements ranging from 25 to 40 percent on various high-value medtech, such as implants.14 Taken in sum, these policies may place U.S. firms at a competitive disadvantage, as they are the leading suppliers of these high-end devices to India’s market (Torsekar, 2017).

Beyond the imposition of NTM’s India has also raised tariffs on medtech during 2016 in an effort to further dampen the country’s import dependence. Medtech tariffs increased from 5 percent to 7.5 percent, with the list of medtech including pacemakers, coronary stents and stent grafts, surgical equipment. In addition, by placing higher tariffs on finished medtech, as opposed to intermediate goods and parts (which are used in the production of finished goods), these policies are expected to further advantage domestic producers at the expense of foreign manufacturers (USTR, 2018, p. 225). While these measures don’t necessarily add to the complexity or extend time to market, it should be noted that policies that benefit local producers at the expense of foreign producers would likely discourage U.S. exports.

3.3 Brazil

3.3.1 Market Overview

Brazil is the largest medical device market in Latin America and was valued at $4.7 billion in 2016 (Emergo, 2017d). During the past decade, Brazil remained a top 15 destination market for exports of advanced medtech from the United States, though a recent economic recession has translated into declining exports for the past five years; according to GTIS (2018), U.S. exports of advanced medtech to Brazil declined by 17 percent during 2012–17 to $1.1 billion. However, the 3 percent expansion of U.S. exports of these products to Brazil’s advanced medtech market during 2016–17 suggests a reversal of the previous five-year trend.

The domestic market for disposables and other low-end hospital equipment is largely supplied by the domestic industry, presenting opportunities for U.S. manufacturers to supply the high-end of the market. The demand for these devices will likely grow as rising incomes in the urban south of the country translate into the emergence of non-communicable diseases (e.g. cardiovascular disease and cancer) which account for nearly three-quarters of deaths in the country (EIU, 2018e; WHO, 2014). As a result, Brazilian imports of diagnostic equipment, ranging from electrocardiographs, MRI machines are all projected to experience the double-digit import growth in both value and quantity in the near future (Roy, 2017).

3.3.2 Regulatory Overview

The process of registering a medical device for sale in Brazil ranked among the world’s most complex, due largely to the frequently changing regulations and a relatively under-resourced Brazilian Health Surveillance Agency (ANVISA) (Emergo, 2017e; Dun, 2015). Brazil regulatory regime ranks among the world’s highest in both complexity and cost (Emergo, 2017a). There are several key measures associated with complying with the country’s medtech regulations. First, exporters need to appoint a Brazilian Registration Holder who acts as a regulatory liaison through the process and obtain a license to sell medtech within the country. This process alone can average more than one-year for the highest risk devices.15 All documents, including product identification, labeling, instructions for use of the product, and legal documentation, device descriptions, and manufacturing stages of the devices, provided during the process must be translated into Portuguese, which can be lengthy.

Next, foreign companies are required to comply with a local quality management system requirement called the Brazilian Good Manufacturing Practice (BGMP) for all devices. However, the most risky devices require an audit by Brazil’s National Health Surveillance Agency (ANVISA),16 and producers need to submit clinical data for regulatory compliance which can be a lengthy process (Emergo, 2017d; USTR, 2016, p. 54). For most implantable devices, the data that is submitted must also include pricing comparisons to other markets where the device is sold, along with pricing comparisons of analogous products that are being sold in Brazil. Further, with regard to testing requirements, Brazil applies a mandatory electrical safety testing and certification standard to selected devices. These requirements have raised concerns from U.S. industry representatives within the past decade as being excessive and unrelated to verifying the product safety (Johnson, 2008, p. 19).17 Reportedly, industry representatives have suggested that these challenges have been less of a problem in recent years.18

Delays in the overall approval process have been compounded by the lack of ANVISA federal inspectors to implement the program; during a 2012 meeting to discuss international TBTs, the EU argued that the timelines for registering medical devices in Brazil were too long, with delays being driven by the failure of Brazilian inspectors to conduct factory inspections of foreign producers in a timely fashion (WTO 2012).19 In particular, the final stages of review can result in significant delays, owing to the backlog of devices under review; the most risky devices can range from 8-15 months, or extend beyond 4 years (Emergo, 2017d). Moreover, backlogs in regulatory inspection procedures have also translated into customs delays for admitting imported medtech into Brazil. For example, in 2016 the time to import medical technology was estimated to be one of the highest in Latin America (Advamed, 2016). U.S. manufacturers have reportedly complained about the extensive documentation, which Brazil requires to import medtech (USTR, 2018, p. 67); the peak time for ANVISA to issue an import license for medtech in 2016 was 60 business days.20 Although ANVISA has recently been able to reduce this delay to a 15 business-day average, they are still not consistently meeting their target of 3-5 days.21 Notably, industry representatives report that Brazil’s medtech market is more accessible to U.S. manufacturers than China’s and India’s, respectively, despite these delays.22

4 Gravity Estimation of Competitiveness

To evaluate import competitiveness for medtech, we employ a gravity modeling approach that estimates the factors that determine trading patterns. The modeling approach identifies and ranks countries based on their global competitiveness as importers given their respective GDPs and relationships such as distance, common languages, and trade agreements with exporters. Countries that import large volumes of medtech given these factors are considered highly competitive while those import relatively little are considered uncompetitive. Using these measures of competitiveness, we calculate an ad valorem equivalent (AVE) trade cost that explains each country’s import activity relative to the most competitive country. To better explain the relative competitiveness of each importer and the implied AVE, we conduct a second estimation that relates the competitiveness of each country with factors that might explain these trends. The results suggest that barriers to importation in the form of long or complicated medtech approval processes significantly decrease the competitiveness of importers.

4.1 Data

The analysis is primarily based on international trade data made available by the United Nation’s Comtrade database.23 The data covers all reported trade in each of 42 different 6-digit, HS12 codes that we have categorized as advanced medtech for the years 2012–2015.24 The trade data is squared so that zero trade flows are reconstructed and included where no trade has been reported. Doing so helps better identify factors that prevent trade from occurring all together. To the trade data, we add a collection of gravity variables from the Dynamic Gravity dataset that reflect relationships between countries (Gurevich and Herman, 2018). These variables include the population-weighted distances, shared common borders, common languages, colonial relationships, preferential trade agreements, and GDP. Together, this results in data used to estimate import competitiveness for 167 countries.

4.2 Estimating Competitiveness

The methodology for estimating import competitiveness follows the work of Fontagn� et al. (2011) who propose the use of importer fixed effects in a gravity model to calculate AVE trade costs. Similar approaches have been taken in several other papers by Park (2002) and Fontagn� et al. (2016), for example. In a gravity model, country fixed effects are used to capture all country-level characteristics that determine trade patterns. These country-level characteristics include factors such as market demand, non-tariff measures, and other forms of restrictions that affect a country’s propensity to import. If factors governing demand have been suitably controlled for outside of the fixed effects, they can be used to analyze aspects of trade restrictiveness and measure import costs.

We begin by estimating a typical gravity model, similar to those described by Fontagn� et al. (2011) as well as numerous general gravity surveys such as those by Piermartini and Yotov (2016) or Head and Mayer (2014). The model takes the following form:

Xijs Y j = exp kaskz ijsk + ν is + μjs + ϵijs . (1)

Trade values from exporter j to importer i in product s are denoted by Xijs. Unlike in many contemporary gravity models, the importing country’s GDP, which is reflective of market demand, is moved to the left hand side of the equation prior to estimation so as to remove it from the importer fixed effect. Doing so improves the connection between the estimated fixed effects and unobserved import restrictions. On the right hand side of the equation, zk denotes a collection of conventional gravity variables as described above, νis denotes an exporter fixed effect, and μjs denotes an importer fixed effect.

A gravity model is estimated for each of the product codes separately using a PPML estimator as described by Santos Silva and Tenreyro (2006). PPML estimation offers several advantages over linear methods such as improved handling of heteroscedasticity and the ability to include zero-trade flows. The results of these estimations are depicted if figure 4, which present kernel density plots for the coefficients of the gravity variables across each of the 42 estimated products. As can be seen from the kernel density plots, the estimated values are generally in line with prior gravity research. Distance is consistently inversely related to trade (the coefficient is less than zero) while belonging to a trade agreement, sharing a common language, sharing a border, or being a colony of the exporter are positively related (greater than zero). Interestingly, the estimates for the effect of being a colony of the importing country features a very wide spread covering both positive and negative values, suggesting that it does not have consistent impact medtech trade flows.

Figure 4: Kernel Density Plots of Estimated Gravity Coecients for Medical Devices
The image contains 6 stacked kernel density plots, depicting the coefficient estimates for trade agreements, common language, contiguity, colony of importer, colony of exporter and distance, respectively.

We use the estimates for the importer fixed effects μjs analyze each sample importer’s relative restrictiveness. The importer fixed effects provide a measure of an importer’s competitiveness given their market size as measured by GDP. Countries with larger fixed effects tend to import more on average than those with smaller fixed effects, which implies that they are relatively more competitive. Because this competitiveness already accounts for market demand as proxied by GDP, we assume that competitiveness is largely governed by unobserved import restrictions. Further evidence supporting this assumption is provided later in this section.

Using the importer fixed effects, we are able to rank countries based on their estimated competitiveness and, implicitly, their estimated restrictiveness. Figure 5 provides a map in which this ranking, averaged across all estimated medical devices, is depicted. A full listing of the overall rankings can be found in table ?? in the appendix. In figure 5, countries are broken into four quantiles such that lighter countries such as Belarus (rank 1), Nicaragua (rank 6) and New Zealand (rank 11) are those that are least restrictive. Darker countries such as China (rank 126), Indonesia (rank 153) and Mali (rank 167) are the most restrictive.25

Figure 5: World map of relative import restrictiveness
A map of the world in which countries are colored based on the restrictiveness quartile that they belong to. Darker countries are more restrictive, lighter countries are less restrictive.  Table 5 in the appendix provides the actual rankings on which this image is based.
Note: 1 denotes the most competitive quartile of importers, 4 denotes the least competitive. Uncolored countries are not ranked due to a lack of available data.

The estimates of import competitiveness highlight that the key markets of Brazil (rank 92), China (rank 126), and India (rank 125), rank relatively poorly compared to the rest of the world. Given a sample of 167, these three are in the bottom half of the countries considered. Given the relatively large GDPs and populations of all three countries, as well as their bilateral relationships with exporters of medtech products, all are expected to import much more than they have been in recent years. These empirical findings are consistent with the factors influencing medtech imports noted in table 2, which suggest that NTMs affecting medtech are particularly severe in these countries compared to others.

In addition to creating a ranking of countries based on estimated restrictiveness, the importer fixed effects can be used to derive AVE trade costs associated with unobserved trade distortions. Fontagn� et al. (2011) do this by comparing each country’s fixed effect with that of the most competitive country and identifying the trade cost that would explain this difference. Because we cannot observe the cost-free importation of medical devices, the use of the least restrictive country as a benchmark for cost-free imports is the best available comparison. As such, all computed cost values are relative to that least restrictive, benchmark country.26 For example, Malawi and Belgium are each benchmark countries in two different product codes. Using this comparison and the structure of the gravity equation, we can calculate an AVE trade cost using the following equation:

AV Ejs = exp μjs - μ*s 1 - σ - 1. (2)

As before, μjs denotes the fixed effect for importer j of product s and μ*s denotes the corresponding fixed effect of the benchmark country. The calculated AVEs can be interpreted in the following way. For product 901839 (a subcategory of medical instruments), Belgium is the least restrictive importer while Brazil has an estimated AVE of about 34 percent. In this case, an additional tariff rate of 34 percent in Brazil above the costs present in Belgium would explain the difference between Belgian and Brazilian imports.

One additional parameter is needed in order to complete the calculation, an elasticity of substitution σ. The elasticity of substitution captures the extent to which an importer is likely to substitute between exports in response to price changes. Because it is not possible to directly estimate an elasticity of substitution using the specification of gravity model employed here, we draw on an estimate from the literature. Specifically, we use a value 0f 8.98, which was estimated for “medical devices” broadly by Caliendo and Parro (2015). While the selection of this elasticity does not affect the general ranking of countries based on restrictiveness, it has a large effect on the magnitude of the implied AVE costs. It is likely that this estimate is too low for any particular product category with in the general grouping of “medical devices”, resulting in particularly large estimated AVEs. Broda and Weinstein (2006) discuss the nature of substitution elasticities as goods become increasingly disaggregated, noting that higher levels of disaggregation result in greater substitutability due to the larger number close substitutes available. Put simply, substituting between products within the category of “medical devices” can be done much more readily than substitution between “medical devices” and some other product category. As such, the AVE estimates we present can be reasonably considered a high end of those face by exporters.

The estimated AVEs, averaged across products, are listed in table 5.27 The average AVEs tend to vary between about 30 percent to 130 percent, suggesting that even in the least restrictive countries, imports of medical devices face costly frictions. Individually, the average AVE for a medical device is about 59 percent, the median value is 55 percent, and the standard deviation is about 42 percentage points. In the key markets of Brazil, China and India, these AVEs are high relative to many other countries, which is consistent with their rankings noted above. The AVE for Brazil is 57 percent, China is 67 percent, and India is 60 percent. As before, all three countries exhibit estimated relative import costs above the median rate, indicating higher restrictions faced by medtech products than in other markets.

4.3 Determinants of Import Competitiveness

A limitation of this method for estimating import competitiveness and AVE costs is that it inherently attributes many aspects of a country’s import size other than GDP and the bilateral gravity variables to unobserved restrictiveness. It may be the case that relatively small import values given market size are the results of factors other than trade restrictions. In order to better validate the notion that our reporter competitiveness measures reflect import costs, we introduce a second regression that tests whether the estimated importer fixed effects, and therefore the calculated AVEs, are related to known restrictions that affect medical device trade.

Heid, Larch and Yotov (2017) note that the literature has long used a two-step approach to estimating the effects of non-discriminatory policies, specifically highlighting the methodologies’ used by Eaton and Kortum (2002), Head and Reis (2008), Anderson and Yotov (2012), and Head and Mayer (2014). In many of these papers, the two stages involve the initial estimation of a structural gravity model with the appropriate fixed effects. Second, the fixed effects are regressed against the policy variables of interest that could not be included in the initial gravity model.

To provide evidence that the estimated import restrictiveness and AVEs of each country described above are related to restrictions rather than demand, we regress the estimated fixed effects of each country and product against a collection of variables that more directly reflect the medtech regulatory environment in each country. The first measure reflects the number of months it takes a medical device to gain regulatory approval for importation in each country. The second measure is a categorical variable that ranks the complexity of the approval process from 1 to 5. Both measures are based on information made available by Emergo Group, a consultancy that gathered this information from nearly 1,000 industry professionals worldwide.28 In both cases, these measures differ based on the country importing the device as well as the device being imported. Each HS code is classified into one of several device classes, which reflect the relative health risk of the device. In general, riskier devices are subject to stricter and lengthier approval processes. In addition to these regulatory measures, we include two measures that are reflective of the demand for medical devices in order to also identify demand influences in the estimated fixed effects. Specifically, these measures reflect the per capita healthcare spending (EIU 2018) and medical device density in each country (CPIA 2013). Due to limitations in the availability of this data, we are only able to study the relationship between them and the estimated fixed effects for a subset of the countries in the first stage gravity estimation.

The estimates for the second stage regression are present in table 3. We report six different specifications testing the robustness of the estimates with several different combinations of regulatory and demand measures. Regressions (1)–(3) include combinations of the two measures of regulatory challenges. Regressions (4)–(6) include the factors that are likely to reflect demand for medtech: medical device density and healthcare spending. Each specification was estimated using OLS. Differences in the number of observations in each specification are due to the availability of data. In each case, we used the maximum number of observations available given the respective data requirements. Because the purpose of these regressions is to show the robustness of statistical relationships rather than to compare models, we believe this is a reasonable approach in this case.

These results provide strong evidence that the competitiveness rankings of countries are reflective of the restrictiveness of each importer rather than demand for medtech. The statistically significant, negative relationship between approval time and importer competitiveness confirms that longer delays in product approval reduce competitiveness. Additionally, we find some evidence that approval complexity reduces competitiveness. Complexity, which is ranked from least complex (0) to most complex (5), appears to have some connection with competitiveness. Lower levels of complexity are associated with higher competitiveness, suggesting that moderate levels of regulation are import promoting. This finding is consistent with the work of Chen et al. (2008) who find that certain policy measures are trade improving because the increase consumer demand for the product. However, level 4 complexity significantly reduces competitiveness. The most restrictive category (5) shows no statistical relationship with competitiveness. The coefficients for medical device density and health care spending are both insignificant, lending support to the assumption that demand factors are being properly controlled for using GDP. Neither factor appears to impact the competitiveness of importers, suggesting that the rankings do accurately reflect trade restrictiveness rather than weak demand for the product.

Table 3: Regression of fixed effects on medical device regulatory and demand measures.
Approval Time -0.16*** -0.16*** -0.16*** -0.14***
(0.04) (0.08) (0.05) (0.05)
Approval Complexity (2) 0.72*** 0.32 -0.14
(0.35) (0.57) (0.61)
Approval Complexity (3) 0.76*** 0.26 -0.16
(0.11) (0.44) (0.42)
Approval Complexity (4) -1.61*** -1.65*** -2.05***
(0.45) (0.70) (0.60)
Approval Complexity (5) 0.23 1.03 -0.48
(0.41) (0.97) (0.59)
Medical Device Density 0.000 0.002 0.002
(0.001) (0.003) (0.003)
Health Care Spending 0.000 0.000
(0.000) (0.000)
Constant -19.28*** -20.62*** -19.42*** -19.18*** -19.96*** -19.37***
(0.21) (0.07) (0.41) (0.27) (0.43) (0.29)
Rˆ2 0.006 0.009 0.017 0.007 0.013 0.006
Obs. 2764 7303 2764 2316 1941 1941

Note: *** p < 0.01, ** p < 0.05, * p < 0.10. Robust standard errors in parentheses.

4.4 Implications for Key Emerging Markets

Our analysis suggests that the United States would likely experience a marked improvement in medtech exports to key emerging markets following the harmonization of regulatory procedures to international standards by these countries. These policies largely pertain to the conformity assessment procedures and technical regulations of China, India, and Brazil, which are characterized by duplicative testing or certifications, redundant clinical trials for high risk devices, and the imposition of onerous labeling standards; each of these requirements likely adds substantial delays to gaining market approval. Further, each of these markets would likely reduce the perceived complexity of their regulatory regimes by adopting registration procedures, such as the Regulated Product Submission (RPS), a document drafted by the IMDRF. In particular, RPS advances an electronic protocol for the submission of registration requests and standardizes the process of obtaining pre-market approvals among markets (IMDRF, 2015). Brazil and China are both members of the forum, suggesting the possibility of adopting these protocols.

Another critical finding from our analysis is that regulatory policies associated with time-delays and complexity are of more importance than demand factors within these markets. As such, key emerging markets with especially low per capita healthcare expenditures, such as China and India, would likely achieve greater import penetration by standardizing their regulatory procedures rather than simply increasing their healthcare spending.

5 Conclusion

As the United States seeks to maintain its competitive leadership within the global medtech industry, the ability to export to key emerging markets will remain an important strategy. Chief among these markets are China, India, and Brazil all three of whom maintained regulatory regimes characterized by either a moderate or high times to market and complexity. Our analysis has found that these regulatory factors exert a statistically significant impact on reducing import growth. The United States, which is the world’s largest single-country exporter of these goods and widely considered the world’s most innovative producer, is uniquely impacted by these market restrictions due to the high opportunity costs incurred from foregone revenue as devices undergo lengthy reviews in foreign markets.

As a consequence, all of these countries ranked in the bottom half of our calculations of the world’s most import competitive markets for advanced medtech, with China and India ranking especially low. This suggests that efforts by the IMDRF (and prior work of the GHTF) to harmonize international standards across global medtech markets are likely facilitate greater global trade for these products. Encouragingly, China, India, and Brazil have each adopted portions of the guidance documents from these committees in constructing their respective regulatory systems (USDOC, 2016).


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Table 4: Medtech Products by HS 6-digit code, product description, and total global trade in 2016 (actual dollars)
HS 6-digit code
Trade Value ($)
300510 Adhes Dressngs Coated or Impreg With Pharma Substs 3,201,771,010
300590 Sterile Surgical Catgut, Similar Sterile Sutur,Etc 3,671,327,509
300610 Sterile Surgical Catgut, Similar Sterile Mater Etc 3,896,848,419
300620 Blood-Grouping Reagents 375,434,186
300630 Opacifying Preparations For X-Ray Examinations Etc. 2,678,230,645
382100 Prepared Culture Media For Devel Of Microorganisms 1,765,260,653
382200 Composite Diagnostic/Lab Reagents, Exc Pharmaceut 22,626,700,000
401519 Gloves, Except Surgical Etc., Vulcan Rubber, Nesoi 4,497,962,713
420600 Articles Of Catgut,For Mfg Of Sterile Surgical Sut 61,206,061
841920 Medical, Surgical or Laboratory Sterilizers 856,961,115
841990 Parts Of Medical, Surgical or Laboratory Sterilize 5,109,526,528
871390 Invalid Carriages, Mechanically Propelled 417,059,634
900130 Contact Lenses 5,097,971,625
901811 Electrocardiographs, and Parts and Accessories 840,650,228
901812 Ultrasonic Scanning Apparatus 3,868,010,497
901813 Magnetic Resonance Imaging Apparatus 4,195,833,524
901814 Scintigraphic Apparatus 324,965,239
901819 Electro-Diagnostic Apparatus Nesoi, and Parts Etc. 8,534,230,304
901820 Ultraviolet or Infrared Ray Apparatus, & Pts & Acc 252,671,071
901831 Hypodermic Syringes, With or Without Their Needles 4,502,403,000
901832 Tubular Metal Needles & Needles For Sutures &Parts 2,413,295,532
901839 Med Needles. Nesoi, Catherers Etc and Parts Etc 23,588,000,000
901850 Other Ophthalmic Instruments & Appliances & Parts 3,662,549,794
901890 Instr & Appl F Medical Surgical Dental Vet, Nesoi 46,239,700,000
902110 orthopedic or Fractre Appliances, Parts & Accessor 8,193,266,851
902131 Artificial Joints and Parts and Accessories Therof 8,691,496,629
902139 Artificial Joints & Parts & Accessories Therof,Nes 11,242,800,000
902140 Hearing Aids 3,762,185,043
902150 Pacemakers For Stimulating Heart Muscles 5,239,728,643
902190 Appliances Worn,Carried,Implanted In Body&Pt,Nesoi 11,743,500,000
902212 Computed Tomography Apparatus 2,841,837,916
902213 Appts Base On X-Ray For Dental, Uses, Nesoi 821,580,865
902214 Appts Base On X-Ray, Medical,Surgical,Vetnry,Nesoi 4,332,388,108
902221 Appts Base On Alpha,Beta,Etc. Radiation,Medical,Etc. 301,444,488
902230 X-Ray Tubes 1,830,476,471
902290 X-Ray/Hi Tnsn Genr Cntr Pnl & Dsk Exm/Trtmnt Tb Pt 6,694,386,764
902511 Clinical Thermometers Liquid-Filled 125,094,373
902519 Clinical Thermometer, Nt Combined W/Oth Inst,Nesoi 2,583,094,128

Source: USITC, Harmonized Tariff Schedule of the United States, 2018.

Table 5: Estimated restrictiveness rankings and ad valorem equivalents (AVE)
Country ISO3 Code
Average Rank
Average AVE
Belarus BLR 1 29.1%
Rep. of Moldova MDA 2 33.5%
Armenia ARM 3 35.3%
Georgia GEO 4 35.1%
Lithuania LTU 5 36.5%
Nicaragua NIC 6 38.9%
Ecuador ECU 7 38.1%
Bolivia (Plurinational State of) BOL 8 38.9%
Netherlands NLD 9 36.9%
Jordan JOR 10 37.8%
New Zealand NZL 11 39.8%
TFYR of Macedonia MKD 12 39.9%
Malawi MWI 13 42.2%
Bosnia Herzegovina BIH 14 40.2%
Saudi Arabia SAU 15 38.9%
Slovenia SVN 16 39.1%
Belgium BEL 17 39.6%
Latvia LVA 19 41.3%
Bulgaria BGR 20 40.1%
South Africa ZAF 22 41.3%
Estonia EST 23 40.8%
Cabo Verde CPV 24 43.7%
Afghanistan AFG 25 27.1%
Namibia NAM 26 42.0%
Venezuela VEN 27 39.3%
Singapore SGP 28 42.3%
Lebanon LBN 29 44.3%
Kyrgyzstan KGZ 30 41.5%
Paraguay PRY 31 46.2%
Czechia CZE 32 42.2%
Samoa WSM 33 46.3%
Ukraine UKR 34 44.5%
Tunisia TUN 35 43.6%
Australia AUS 36 42.9%
Uruguay URY 37 41.2%
Hungary HUN 38 41.6%
Costa Rica CRI 39 48.1%
China, Hong Kong SAR HKG 40 47.6%
Kazakhstan KAZ 41 45.2%
Croatia HRV 42 46.5%
United Arab Emirates ARE 43 44.5%
Palau PLW 44 44.1%
Zimbabwe ZWE 45 48.0%
Malaysia MYS 46 45.7%
Portugal PRT 47 43.5%
Viet Nam VNM 49 46.1%
Serbia SRB 50 45.0%
Barbados BRB 51 49.2%
Russian Federation RUS 52 43.4%
Slovakia SVK 53 45.2%
Mongolia MNG 54 46.4%
Finland FIN 55 49.5%
Colombia COL 56 44.4%
El Salvador SLV 57 48.8%
Mauritius MUS 58 51.8%
Iceland ISL 59 45.2%
Thailand THA 60 47.6%
Sweden SWE 61 44.6%
Rwanda RWA 62 52.9%
Maldives MDV 63 58.1%
Kuwait KWT 64 46.2%
Ireland IRL 65 48.1%
Fiji FJI 66 61.5%
State of Palestine PSE 67 51.4%
Chile CHL 68 50.5%
Belize BLZ 69 59.4%
Japan JPN 70 49.1%
Turkey TUR 71 48.5%
Germany DEU 72 49.0%
Israel ISR 73 50.1%
Spain ESP 74 48.0%
Denmark DNK 75 52.0%
USA USA 76 48.1%
Austria AUT 77 50.0%
Argentina ARG 78 51.6%
Bahrain BHR 79 49.2%
France FRA 80 48.4%
Nepal NPL 81 54.5%
Poland POL 82 50.4%
Seychelles SYC 83 64.9%
Burundi BDI 84 62.5%
Guyana GUY 85 60.1%
Jamaica JAM 86 61.4%
Dominican Rep. DOM 87 54.9%
Saint Lucia LCA 88 55.8%
Italy ITA 89 49.5%
Greece GRC 90 52.0%
Switzerland CHE 91 52.5%
Mozambique MOZ 92 58.2%
Cyprus CYP 93 50.7%
Botswana BWA 94 59.3%
Brazil BRA 95 56.8%
Peru PER 96 53.4%
Oman OMN 97 54.4%
Ethiopia ETH 98 57.2%
Suriname SUR 99 58.5%
Malta MLT 100 55.6%
Uganda UGA 101 65.8%
Tonga TON 102 62.5%
United Kingdom GBR 103 54.3%
Canada CAN 104 52.8%
Sri Lanka LKA 105 58.5%
Togo TGO 106 67.1%
Antigua and Barbuda ATG 107 61.8%
Burkina Faso BFA 108 71.3%
Senegal SEN 109 58.5%
Rep. of Korea KOR 110 59.8%
Egypt EGY 111 56.5%
Bermuda BMU 112 58.5%
Azerbaijan AZE 113 56.6%
Angola AGO 114 61.1%
United Rep. of Tanzania TZA 115 65.1%
Sao Tome and Principe STP 116 61.4%
Trinidad and Tobago TTO 117 55.2%
Algeria DZA 118 57.6%
Guatemala GTM 119 57.9%
FS Micronesia FSM 120 72.8%
Bahamas BHS 121 58.3%
Norway NOR 122 55.6%
Zambia ZMB 123 64.8%
Greenland GRL 124 68.0%
Morocco MAR 125 59.8%
Romania ROU 126 58.0%
Brunei Darussalam BRN 127 61.3%
India IND 128 60.2%
China CHN 129 67.0%
Andorra AND 130 73.3%
Gambia GMB 131 70.3%
Central African Rep. CAF 132 60.4%
Albania ALB 133 63.9%
Yemen YEM 134 65.3%
Kiribati KIR 135 70.2%
Cote d’Ivoire CIV 136 72.6%
Niger NER 137 78.2%
Qatar QAT 138 66.0%
Honduras HND 139 67.6%
Sierra Leone SLE 140 68.2%
Mexico MEX 141 64.1%
Panama PAN 142 65.9%
Madagascar MDG 143 73.6%
Luxembourg LUX 144 70.5%
Saint Vincent and the Grenadines VCT 145 70.7%
Cambodia KHM 146 73.5%
Ghana GHA 147 85.2%
Guinea GIN 148 88.6%
Cameroon CMR 149 84.9%
Mauritania MRT 150 80.2%
Dominica DMA 151 83.1%
Congo COG 152 91.8%
Pakistan PAK 153 81.9%
Bangladesh BGD 154 83.7%
Papua New Guinea PNG 155 97.8%
Indonesia IDN 156 78.5%
Kenya KEN 157 78.7%
Benin BEN 158 106.4%
Philippines PHL 159 78.3%
Myanmar MMR 160 117.8%
Comoros COM 161 122.4%
China, Macao SAR MAC 162 95.0%
Lao People’s Dem. Rep. LAO 163 105.9%
Sudan SDN 164 111.2%
Iraq IRQ 165 132.0%
Solomon Isds SLB 166 125.9%
Lesotho LSO 167 119.8%
Nigeria NGA 168 113.4%
Bhutan BTN 169 119.4%
Mali MLI 170 119.7%
Note: The average rank and AVE are both independently calculated across all
product codes and may not perfectly align. Because of the variance in estimated
AVEs, a country’s AVE may be slightly higher or lower than the countries ranked
higher or lower that it.

1Similar gravity methods were used by USITC (2018).

2Because tariffs are generally low with respect to the global trade of medtech, trade costs in this context largely refer to non-tariff measures (NTMs), particularly in the form of onerous regulatory requirements that restrict trade. Examples include duplicative product testing, redundant clinical trial data submissions, and an inadequate pricing and reimbursement system (Johnson, 2008; Sunesen, 2009). These NTMs produce regulatory environments that correspond to high approval times, are costly to comply with, and are characterized by complexity. For example, imported medtech in China may face approval times that are more than double the global average of 10 months, generated more than $50,000 in compliance costs, and were listed (alongside Brazil) as the among the world’s most complex (Emergo, 2017).

3However, variations in the categorization of devices varies across countries. For example, in the United States, the Food and Drug Administration (FDA) identifies three classes of medtech, which range from basic hospital supplies and other disposables (class I), to therapeutics and other devices that carry slightly elevated health risks but are similar to existing devices on the market (class II), to diagnostic devices which exhibit a high risk of injury or illness to a patient (class III).

4The most common QMS in the medtech industry is the ISO 13485 certification, which satisfies most of the quality assurance requirements for regulatory approval in the EU (BSI, 2016, p. 5).

5Industry representative, e-mail correspondence with authors, August 20, 2018.

6According to Emergo Group, the EU’s maximum time to market estimates for the highest risk medtech was 9 months in sharp contrast to Japan (16 months), China (22 months), and the United States (30 months), for example.

7A strengthening U.S. dollar makes U.S. goods relatively more expensive and generally translates into reduced sales and revenues in overseas markets. Conversely, U.S. medical device OEMs benefit from a weakening U.S. dollar when entering foreign markets.

8For example, both countries fell within the top ten of medical device density out of the 67 countries profiled in a study (CHPI, 2013), suggesting relatively saturated medical device markets.

9As of 2018, the United States’ exports of medtech to each of these countries was: India (26 percent), Brazil (31 percent), and China (33 percent).

10Urbanization is often associated with many public health risks—including various non-communicable diseases such as lung cancer, cardiovascular disease, diabetes, and hypertension. These risks largely reflect the increased consumption of high-calorie, processed foods; the transition away from farming towards more sedentary occupations; and the relatively poor air quality that often accompanies city living (Torsekar, 2014).

11Officially known as Order No. 650, the Regulations for the Supervision and Administration of Medical Devices.

12Industry representative, e-mail correspondence with authors, August 28, 2018.

13It should be noted that price controls are classified as a type of NTM that is distinct from the conformity assessment procedures discussed earlier (UNCTAD 2012).

14Industry representative, e-mail correspondence with authors, August 28, 2018.

15Industry representative, e-mail correspondence with author, August 7, 2018.

16Brazil uses a similar risk based classification as the EU and categorizes devices into four classes.

17Industry representative, e-mail correspondence with author, August 7, 2018.

18Industry representative, e-mail correspondence with authors, August 20, 2018.

19Industry representatives note that this has been less of a problem in recent years. Industry representative, e-mail correspondence with authors, August 20, 2018.

20Industry representative, e-mail correspondence with author, August 7, 2018.

21Industry representative, e-mail correspondence with authors, August 20, 2018.

22Industry representative, e-mail correspondence with authors, August 20, 2018.

23United Nations Statistics Division. UN Comtrade.

24The years 2012–2015 were chosen based on the availability of HS12 classified trade data, available after 2012, and GDP data, which was only widely available up to 2015 at the time of writing.

25Uncolored countries are those for which insufficient data was available for estimation.

26That is, the AVEs are effectively normalized to the benchmark estimated AVE countries. The benchmark country will have an AVE cost of zero percent and estimates for other countries should be interpreted as being in addition to the unidentifiable AVE of the benchmark.

27A more complete listing of computed AVEs by country or product is available by request.

28These data are available at the Emergo website: