Unleashing China and India’s growth potential (1): productivity growth

China and India rank 1^st and 3^rd, respectively, on the list of largest economies in the world[1]. Their contribution to global growth has increased from roughly 25% during the 1990s to almost 60% in 2016 (Figure 1) and their importance for the world economy in terms of trade and investment will continue to grow.

[1] Measured in purchasing power parities (PPP).

Looking back, especially China has realized extraordinary annual growth rates of gross domestic product (GDP) per capita (7.7% over 1970-2016, Figure 2). During this period, China outperformed India by almost a factor two. The tide seems to be turning, though, as the Chinese economy is expected to shift to lower growth rates (see Erken and Blaauw, 2016), while India is speeding up and will expectedly continue to do so in the future (Figure 3). As a result of strong economic performance and very large populations, the middle class and its purchasing power is rising in both China and India. International investors and companies are keen to grasp investment and business opportunities in these highly-dynamic economies and large potential markets.

In two complementary reports, we compare the fundamental growth drivers of China and India and the challenges for the future. In this report (part one of the diptych), we focus on productivity developments, whereas in the second report (see Giesbergen et al., 2017), we compare the institutional strengths and weaknesses of the two countries and the implications thereof for future growth.

We believe both China and India will face a major challenge in their development from an emerging market to an industrialized country. They have to maintain high economic growth levels to avoid the so-called middle income trap: the phenomenon that economic growth falls significantly after a certain threshold is reached (see Eichengreen et al., 2013). This threshold lies between USD 12,000 and USD 18,000 per capita (2015 purchasing power parities)[2]. In order to keep growth on high levels, a transition to higher labour productivity is necessary[3].

An assessment of economic performance – drivers of economic growth

A breakdown of GDP per capita shows that GDP per capita in China is substantially higher than in India due to higher labour productivity levels, as well as a markedly higher labour participation (Table 1). The amount of hours worked per worker is almost equal in both countries.

[2] The threshold by Eichengreen et al. (2013) lies between USD 10,000 and USD 15,000, measured in 2005 PPP.

[3] This is because growth in emerging markets is often resource-driven, dependent on cheap labour and capital growth. When wages start to rise, the emerging economy loses its comparative cost advantage and thus its competitive edge.

From an international perspective, however, levels of productivity in China (€11 per hour) and India (€7 per hour) are both relatively low. These levels are registered at the low end of the distribution and comparable to for instance, Nigeria (€10) and Pakistan (€7). It also implies that there is much room for improvement. As a reference, productivity per hour in the US and the Netherlands is €62.

In countries with much higher levels of productivity, total factor productivity (TFP)[4] has been an important contributor to productivity gains. In contrast, China and India have mainly achieved higher productivity by investment in non-IT capital goods, e.g. machinery, transport equipment and real estate, while the contribution of total factor productivity has lagged behind (Figure 4 and 5). This is not a sustainable strategy. Although investment generate large productivity gains in the first stages of development, these gains are subject to diminishing returns, i.e. the gains of additional investment becomes smaller and smaller. To be more specific: once a high-quality infrastructure has been put in place, additional investment in, for instance, more roads, railways and high-speed trains will hardly generate positive economic effects. Although India still has much headroom to raise growth by increasing investment (because, e.g., it lacks a proper infrastructure), for China ongoing large-scale investments are less desirable. Erken and Kalf (2016) show that additional lending (and thus investment) to the Chinese corporate sector seems to have a continuously lower effect on growth of value added.

[4] TFP is the part of value added growth which cannot be attributed to additional usage of labour and capital in the production process. In short, it is a broad measure of the efficiency of an economy.

Explanation: computed annual growth rate of labour productivity per hour, contributions of components in percentage points.

To avoid the middle income trap, China and India ultimately will have to move up the value chain. Therefore, the focus should lie on boosting investment in human capital, technological capital and innovation (that will in turn boost TFP) (Eichengreen et al. (2013a), Erken et al. (2016), Griffith et al. (2004) and Cameron et al. (2005), Figure 6).

Chinese and Indian innovative capacity across the board is relatively limited from a global perspective. Although China outnumber ed the US in terms of patent applications (800,000 versus 285,000 in 2014), these patents encompass inventions that are new to the Chinese economy, but not necessarily new to the world. Therefore, it is more relevant to look at the number of applied patents at the US Patent and Trade Office (USPTO). These exclude patents which are: a) novel to a country, but already discovered elsewhere and b) inventions not worthwhile patenting internationally (see Porter and Stern, 2000). USPTO data shows that in 2015 roughly 8,000 applied patents where filed by Chinese parties, against, for instance, 52,000 from high-tech neighbour Japan.

If we compare the knowledge stock among Asian countries (see Erken (2017) for the calculations) China and India perform poorly with roughly 5 unique inventions per 100,000 people active on the labour market (Figure 7). In comparison, Japan has 430 unique inventions in place, and South Korea somewhat more than 255. Furthermore, China (25) and India (66) rank fairly low on the Global Innovation Index.

Causes for low innovative capacity

A first reason why China and India’s innovative capacity and their overall labour productivity are low, is related to education. The average duration of education[5] in China is 7.5 years, which is considerably lower than the overall average (Figure 8). Human capital in India is even further below average and more or less equal to for example Honduras, Algeria, and Uganda. More specifically, only 2.4% of the Chinese population older than 25 years has completed tertiary education, which is lower than in India (6.1%) and substantially lower than the more prosperous Asian countries, such as Korea (35%) and Japan (20%). There is an additional aspect of the education system that is holding back innovation. The Chinese and Indian education systems put a lot of emphasis on memorization and test taking. For China, this pays off tremendously well in international benchmarks, such as the international PISA student skills survey (Programme for International Student Assessment). The downside, however, is that such an education system is less supportive of generating creativity and problem solving skills (see Zhao, 2015).

Second, when assessing the quality of universities (see QS World University Rankings), China has three universities in the top 50 (Tsinghua, Fudan and Peking University), whereas the first Indian university can only be found on spot 152 (Indian Institute for Science). No Chinese universities rank top 20 though, which is another indication that China is also not operating at the technological and scientific frontier. Moreover, Chinese and Indian universities have weak linkages to industry, and consequently, there are insufficient public-private collaborations to foster innovation. In the Global Innovation Index, China ranks 31 and India 49, respectively, on the indicator university/industry research collaboration.

[5] The average years of education is an indicator often used to measure the amount of human capital in a country (see Barro and Lee, 2013).

A third explanation for the low level of innovation is that intellectual property rights (IPR) are often violated without sufficient repercussions by the authorities. This is detrimental for innovation. China and India have been on the US’s Priority Watch List on major intellectual property violators since the onset of the list in 1989. In the 2016 report, the US Trade Representative expressed that the violation of intellectual property rights is one of the main concerns in India is in the pharmaceutical industry. According to the report, studies estimate that up to 20% of drugs sold in India are counterfeit. Main concerns related to violations of intellectual property rights for China include, among others, trade secret theft, piracy and counterfeiting.

Fourth, Research & Development (R&D) investment as a % of GDP (the R&D intensity) in India is low relative to its economic size, being outpaced even by sluggishly growing emerging markets such as Brazil (Figure 9). China, on the other hand, has been able to crank up R&D investment (as a percentage of GDP) to levels equal to that of the EU. A problem in China, however, is that a relative small proportion of the R&D investments are dedicated to basic research (4%) compared to most OECD countries (17%) and R&D is heavily oriented to infrastructural knowledge, such as buildings and equipment (see OECD, 2016). In any case, there are doubts if the current R&D levels in India and China will suffice in order to avoid the middle income trap, as two prime examples which managed to achieve this, i.e. Japan and South Korea, have been investing substantially larger shares of their GDP into R&D.

Fifth, in China the strong state-led intervention of the government in the economy causes capital misallocations and disrupts price competition. Consequently, private fast-growing innovative firms have difficulties competing on the internal market against inefficient state-owned enterprises (SOEs) and bank funding is also largely calibrated towards these SOEs. This goes at the expense of a favourable entrepreneurial environment and Schumpeterian creative destruction, which is necessary to foster TFP gains (Erken et al., 2016). Although India’s market-based economy differs from China’s state-led, an unfavourable regulatory environment also discourages R&D expenses and innovation.

Last but not least, one important factor for enhancing R&D as well as broader innovative capacity investment is related to inward foreign direct investments (FDI), as this provides opportunities for technological catching-up. An important turning point for inward FDI in China was the signing of WTO membership in 2001. The membership generated deregulation in terms of elimination of foreign capital regulations in services industries like finance and distribution. Nowadays, inward FDI in China reaches a breadth of industries ranging from manufacturing industries to trade and services (Figure 10). The countries which comprise the highest shares of FDI in China are Hong Kong, the British Virgin Islands, Singapore, Republic of Korea and Japan (Figure 11).

The Indian government began relaxing foreign investment regulations since the early 2000s, installed so-called special economic zones in 2005 and developed industrial parks to attract foreign investments to its manufacturing industries, resulting in investment having grown rapidly since 2006. India’s inward foreign investments are primarily in the telecommunications, broader service and trading sectors (Figure 12).

Going forward, both India and China have to keep economic growth on high levels in order to circumvent the so-called middle income trap. Therefore a transition to higher labour productivity is necessary. Some countries, such as Japan, South Korea, Singapore and Ireland, have been successful in avoiding the middle income trap by successfully transforming their economy. Others, such as Brazil, Thailand and Mexico have been less fortunate. Erken (2017) has calculated the effect of these factors on total factor productivity for a specific panel of countries, which have started from a low income level and achieved considerable growth rates over time, but either got stuck in the middle income trap or were successful in avoiding it. The model shows that technological capital, technological catching-up, human capital, freedom to trade internationally and regulatory quality are important factors of productivity growth.

Erken (2017) has used this model to calculate the labour productivity effects in different scenarios for India and China up till 2025. In a relative conservative scenario, patent capital is raised to the level of Singapore (123 patents per 100,000 persons employed), the tertiary duration of education is raised to the level of Japan (1 year), the level of openness of trade is raised to the level of Greece and Costa Rica and the quality of regulation to the level of Portugal. Although this policy agenda is ambitious, countries that avoided the middle income trap, such as South Korea, Japan, Ireland and Taiwan developed much faster on these determinants. See Erken (2017) for an elaboration on the assumptions. If China and India could reach these parameters in 2025, both economies would reap substantial welfare effects. Chinese labour productivity levels per hour would rise from roughly USD 11 in 2016 to almost USD 20 in 2025, which is USD 3.7 higher than in the baseline scenario (Figure 13). Although this effects seems limited, it has tremendous wealth effects, as it would add an additional USD 6.5trn to the Chinese economy (USD 3.7 times 1770bn hours worked a year). For India, the level of productivity per hour could increase from USD 7.5 to USD 12.5, which is equivalent to USD 3.1trn annually (Figure 14). In an extreme scenario where both economies would follow-up on the innovative trailblazers in Asia[6], labour productivity per hour in China would go up to USD 27 and in India to somewhat less than USD 15. This is equivalent to USD 19trn of additional wealth in China and USD 6trn in India, which is roughly equal to US GDP now.

[6] This scenario would imply raising relative patenting levels to that of Taiwan (500 per 100,000 persons employed), boosting tertiary education to levels of South Korea (1.5 years of average tertiary education). Finally, the institutional framework would be changed to the standards of Hong Kong. See Erken (2017) for an elaboration on the assumptions.

Policies

China has an ambitious policy agenda to push technological development. The 13th five year plan adopted in March 2016 emphasizes the role of the high-tech sector to create growth and to rebalance the economy. Even some specific goals are mentioned: Research and Development (R&D) spending should be 2.5% of GDP and the number of patents per 10,000 persons should increase to 12. In some fields, such as renewable energy, information technology, biotechnology and new materials, China is supposed to be operating at the technological frontier. Other initiatives, such as the National Science Fund for Distinguished Young Scholars and the Thousand Talents Plan, aim at fostering scientific young talent and repatriate them from abroad and encourage them to work in China. Indeed, some highly-profitable multinationals emerged over the past years, such as Huawei in telecommunications, Baidu and Alibaba in internet services and Lenovo in laptops. Gupta and Wang (2016) nevertheless illustrate that there are many aspects of the Chinese innovation environment that need improvement.

In 2015, the Indian government has launched the Atal Innovation Mission (AIM), a programme which provides funds to institutions involved in research and innovation. Although India’s policy think-tank NITI Aayog has initiated first steps, many aspects of AIM have to be articulated. Furthermore, India has launched a new Intellectual Property Rights policy, addressing six main categories: patents, copyright, trademarks, trade secrets, enforcement, and international treaties. Given India’s bureaucratic and complicated legal system, however, it will take a while before the policy will translate into actual legislation and generate positive effects on R&D investment and innovation. Lastly, there are many initiatives like Startup India, Digital India, R&D tax breaks and other incentives to foster innovation (see Dhar and Saha (2014), India Government and Startup India for an overview of India’s innovation and entrepreneurship policy).

Given the sheer of India and China, both countries have the advantage that the government can intensify its role as so-called launching customer in order to boost innovation. Moreover, the government could showcase digitalisation and innovation itself, which will spill over to the lives of millions and aid to the adoption and creation of new technologies. It remains, however, to be seen if the current innovation policies in China and India are sufficient to push the technological envelop in the future, or if these countries will continue to merely adopt existing technologies and produce incremental innovations.

Given their highly dynamic economies and large potential markets, international investors and companies are keen to grasp investment and business opportunities in China and India. There is a risk, however, that both countries will get stuck in the so-called middle income trap. This means that countries that have realised fairly high growth rates in the past experience a substantial cooling down of economic growth after certain prosperity levels are reached (between USD 12,000 and USD 18,000 per capita). It is crucial for countries to shift to higher productivity growth in order to avoid this middle income trap. Countries that have been successful in circumventing the middle income trap, such as Japan and South Korea, have boosted productivity by fostering innovation, human capital and institutional quality. China and India still lack a highly educated work force and meaningful innovative capacity. If both countries implement an ambitious innovation and education agenda in combination with an improvement of their institutional context, these countries are able to reap substantial productivity gains. Under relative conservative assumptions, Chinese labour productivity levels per hour could rise from roughly USD 11 in 2016 to almost USD 20 in 2025, which would add USD 6.5trn of total value added to the Chinese economy. For India, the level of productivity per hour could increase from USD 7.5 to USD 12.5, which is equivalent to USD 3.1trn of total additional value added. The additional value added in both countries together (USD 9.6trn) is roughly equivalent to half of total US GDP today (USD 18trn, 2015 USD PPP). In short, both countries have the capacity to become the world’s new global growth catalysts, which is welcome in a time where the US is more and more reluctant to fulfil its role as global leader of the pack.