The Deloitte Research Monthly Outlook and Perspectives


The Deloitte Research Monthly Outlook and Perspectives

Issue 65

17 June 2021


China to resist forced RMB appreciation

Will the RMB continue to strengthen against the US dollar? How could China avoid adverse effects arising from unprecedented monetary easing in the world's most developed economies? These two questions are related. The RMB's strength against the dollar has been driven by large interest rate differentials which make the RMB a high-yielding currency in an ultra-low interest rate environment. Despite a strong global economic recovery, mainly led by the US and China, the Federal Reserve is expected to keep the Fed Fund Rate unchanged this year at a time when China faces more inflationary pressure due to 1) a potent recovery in the wake of the pandemic, and 2) surging commodity prices. However, given that the dollar is the most dominant reserve currency in the world, the US could easily get away with the Fed's dovish stance, at least in the short run. In other words, a weak dollar has not resulted in inflation in the US. As Richard Nixon, the 37th President of the US famously put it, "the dollar is our currency, but it's your problem".

This spillover effect of such unorthodox monetary easing led by the US has put China in a less than comfortable position. Should and will China start a cycle of monetary tightening? If so, what tools should the People's Bank of China (PBOC) use for draining excess liquidity? So far, the PBOC has signaled no change on interest rates. Of course, one could argue for the merit of a stronger RMB to fend off imported inflation. The most important reason for keeping interest rates stable for China is high leverage (enterprises and local governments). An abrupt change to the cost of capital could result in financial sector dislocation, especially after the property market has had a powerful run in some major cities (e.g., Shenzhen and Shanghai) since 2019. In addition, if interest rate differentials between China and the US are widened further, would investors take bigger gambles on a strengthening RMB? But higher commodity prices have not resulted in higher prices of downstream sectors in China, reflecting strong competition in the manufacturing sector (the PBOC's latest forecast for CPI in 2021 is 2%). If firms can't pass higher costs onto consumers, a stronger RMB, which would do little to alleviate the profit squeeze, could well erode firms' competiveness. Conventional monetary tightening tools of a higher interest rate or a firmer exchange rate are therefore not optimal policy responses for China at this juncture.

Chart: Divergence between CPI and PPI signals profit squeeze

Source: Wind

To quote Guo Shuqing, Head of the China Banking and Insurance Regulatory Commission (CBIRC), "massive money printing by developed countries is the source of global inflation while goods which are being produced by millions of Chinese producers are an anchor to stabilize global inflation" (Lujiazui Forum, June 10, 2021). Indeed, policymakers have increasingly exhibited their uneasiness towards the one-way appreciation of the RMB. The move taken by the PBOC on June 15 to raise reserve requirement ratio of foreign currencies was clearly aimed at reducing carry yields of holding RMB. Subsequently, several policymakers have downplayed the potential appreciation of the RMB. For example, Hu Xiaolian, former Head of the State Administration of Foreign Exchange (SAFE), has said that the RMB's internationalization is only at a very initial stage. Guo Shuqing has even said that investors should be aware of the risks of speculating with currencies, derivatives, commodities, gold and real estate. Also at the Lujiazui Forum, Pan Gongsheng, Deputy Governor of the PBOC, explicitly stated that two-way fluctuations of RMB exchange rate will be the new normal going forward.

What's the best policy response for China to mitigate the spillover effect from unorthodox monetary easing? In the long run, to internationalize the RMB by developing it into a major reserve currency would be the ultimate solution. Yet, such an approach will take many years. In the short run, the messages from the Lujiazui Forum are crystal clear: 1) not to fall into a forced appreciation trap which will adversely affect the real economy, and 2) to increase the role of capital markets so that direct financing will play a much greater role in the economy. But a much larger role of direct financing (equities and debt) must be achieved with a faster pace of financial sector liberalization. One of the key lessons from the Asian Financial Crisis was that East Asia ought to develop a deep local currency market so that domestic savings could be channeled more efficiently into the real economy. In practice, however, the development of the local bond market in most Asian economies has been much slower than policymakers envisaged for various reasons over the past 20 years. For China, such urgency should be more acute because a strong RMB may result in a minor current account deficit which, by default, requires external financing. That is why a faster pace of financial liberalization is called for.

Chart: Share of international payments among major currencies underscores early stage of RMB's internationalization

Source: Wind


Speeding up AI adoption in the semiconductor industry

The global race to achieve pre-eminence in artificial intelligence across a spectrum of industries has increased its momentum. Not only have brands such as Apple and Samsung introduced AI functionalities in their smartphones, but the commercial drone market has also shown substantial AI driven growth. At the same time, healthcare and other industries are also accelerating the adoption of AI technology.

The semiconductor industry is latest industry to add AI to its production processes. Artificial intelligence has been permeating all levels of the semiconductor value chain in new ways, the most important of which is to improve the semiconductor design and manufacturing process. AI can apply machine learning, neural networks and other algorithms to processes such as wafer defect detection and classification, chip manufacturing and modeling, photoresist contour prediction, wafer process control/monitoring and other semi-conductor manufacturing processes.

However, current levels of AI in the semiconductor industry leave much to be desired. One reason for this is that due to the complexity of the semiconductor production process and the high level of specialization, the application of AI technology in semiconductor production lines needs more time to be properly integrated. We believe that semiconductor companies should consider the following three points before allocating resources for AI technology:

First, before the application of AI technologies, semiconductor companies need to adjust their business and production strategies. Competition in the semiconductor industry has become increasingly fierce as demand is constantly rising. Semiconductor companies need to formulate new strategies to maintain their competitiveness. For this they should be focussing on identifying which parts of the production process would most benefit from the integration of AI and create an AI roadmap that is tailor made to their needs. For this companies should accurately assess the scale and importance of related businesses according to use, time value and feasibility. After drafting business plans based on these indicators, semiconductor companies need to create AI road maps and allocate resources for AI based on their particular road maps. In terms of external resources, semiconductor companies can actively seek help from other industries and use external resources to develop AI. At the same time, semiconductor companies can accelerate their own R&D capabilities and find opportunities to collaborate with AI companies. A fully supported R&D and manufacturing ecosystem can be achieved by sharing resources amongst firms through collaboration.

Second, there is a lack of AI talent with an understanding of the semiconductor industry. For AI to be introduced in all facets of the semiconductor value chain from design to manufacturing, professionals in the field of AI with an understanding of the semi-conductor industry are urgently needed. This has led to an explosion in the demand for AI talent in the semiconductor industry and therefore, semiconductor firms need to be on the lookout for talented manpower in AI and machine learning areas to assist companies in technical research and experiments. At the same time, it is necessary to clarify and specify the roles and responsibilities of different members of the team so that each person knows what is expected of them and can function well. Since the integration of AI in semiconductor companies requires much greater coordination among various departments, semiconductor companies should also train AI teams to become cross-functional, multi-task teams. It would be wise to bring talented people from other departments into the AI team to do this. This would permit better control of the core resource of a company’s internal projects and assist in the application of different AI technologies to the development of the company.

For AI to be integrated into the production chain of the semiconductor industry, companies need to restructure their internal processes and chains of command, integrating the AI team into the core of its production and decision-making processes.

Finally, more technical expertise is required in the application of AI. The semiconductor manufacturing industry is highly specialized, and the customization of integrated circuits requires very high standards in semiconductor production. Independent AI systems may need to be established in all aspects of semiconductor production and manufacturing. Currently, AI is mainly used in fields that are easy to replicate and promote, such as automated verification and predictive maintenance. More technical support is required for the development of program design of a single corresponding system in each of the links in the semiconductor value chain. In addition, AI often relies on high-quality training data to improve efficiency and product quality in semiconductor production. Hence semiconductor companies need to support the training of AI models by obtaining a large amount of experimental data of AI models so as to improve the accuracy and efficiency of such models.


Navigating the uncharted waters of carbon neutrality

Ever since China committed to cutting CO2 emissions, all sectors of the economy are rapidly formulating strategies for decarbonisation. The auto industry, however, seems to have been lagging a little behind the others – perhaps out of a sense of complacency or out of a certain feeling of helplessness, born out of the fact that it sources materials and components from a very wide range of producers working in diverse sectors, and so cannot easily map its carbon footprint. In this piece, we are going to try to answer the question: where are the CO2 emissions coming from in the auto industry? The answers we have arrived at may surprise some of our readers.

Before we dive into the details, however, here are a few key facts and figures to keep in mind:

  • The transport sector is responsible for only 9% of China’s total CO2 emissions, among which more than 70% comes from road transportation.
  • Emissions levels from different forms of transportation vary significantly, with passenger cars taking the lead and contributing 44% of total CO2 emission in road transport. Heavy duty trucks, despite  their small fleet size (less than 7% of total car parc), are also major polluters, accounting for 41% of total CO2 emissions1

Chart: Transport sector CO2 emissions by mode

Data sources: WRI, NDRC, CICC; Note[1]: excludes bikes and motorcycles

Fossil fuel is the primary source of CO2 emissions from road transport. But to thoroughly evaluate all the environmentally significant effects of motor vehicles, we need to factor in the entire production and marketing process, including energy source-related emissions (i.e. fuel or electricity powering the vehicles) and manufacturing-related emissions (from raw material extraction, components production, vehicle assembly, transport, vehicle use and recycling). To get a true picture of CO2 emissions in the auto industry, it is imperative to look at the life-cycle of vehicles and then to build solutions based on this perspective.

Lifecycle carbon emissions of vehicles have the following characteristics.

  • CO2 emissions stemming from fuel production and utilization cycle outweigh those coming from the vehicle manufacturing cycle. However, the percentage varies depending upon the types of fuel used by the vehicles. For gasoline vehicles, the fuel cycle (extracting crude oil from the ground, transporting it to a refinery, refining the crude into gasoline, and transporting the gasoline to service stations, burning gasoline while driving) comprises more than 80% of total CO2 emissions. For battery-powered vehicles, electricity generation and distribution make up of 54% of total CO2 emissions.
  • Seen from an life-cycle perspective, battery-powered vehicles are not as clean as most people believe even though they have no direct emission from tailpipes and use energy more efficiently than gasoline vehicles. This is because in China’s case, coal-fired power still accounts for nearly 70% of the nation’s total electricity generation. Hence charging batteries with coal-generated electricity has made electric vehicles less environmentally friendly than their Western counterparts.. In addition, heavily polluting processes of manufacturing battery materials (i.e. aluminium smelting) add to the emissions burden of manufacturing battery materials (i.e. aluminium smelting) add to the emissions burden of electric vehicles.
  • Throughout the process of vehicle production, raw material extraction is responsible for the single largest share of CO2 emissions. Battery production is extremely polluting and contributes 50% of the total CO2 emissions of EV production. As for gasoline vehicles, the effort to increase fuel efficiency by using lightweight materials has inevitably added to its share of CO2 emissions.

For now, decarbonization efforts mainly target the fuel cycle, in particular the reduction of the driving footprint in order to minimize carbon emissions from motor vehicles. Current decarbonization efforts fall into three categories: reducing total driving, encouraging a cleaner way of travelling and using energy more efficiently. Reducing travel demand includes encouraging people to drive less and making driving more expensive. Cleaner ways of travelling includes taking public transportation over private vehicles as the primary mode of travel.

In the case of cargo transport, encouraging intermodal rail to minimize truck transportation. Technology innovation includes increasing fuel efficiency, reducing EV’s green premium (the extra cost that a consumer has to pay for a product that emits less CO2) and switching to alternative fuels with low carbon density (i.e. biofuels) .

We believe, however, that this is not enough, and that reducing CO2 emissions in vehicle production should also be targeted. From a life cycle perspective, while gasoline vehicle production is polluting, electric vehicle production is twice as polluting. It’s estimated that the life cycle CO2 emissions from EV production is at roughly 12 tons whereas ICE vehicle production produces about 6 tons CO22. The disparity is mainly due to the way in which the EV battery is produced, a highly energy intensive process.

For car manufacturers and companies up and down the auto industry food chain, it is crucial to make a full life cycle assessment of their carbon footprint, beginning with raw material extraction, followed by manufacturing, distribution, and consumption, and ending up with re-use, recycling of materials, energy recovery and ultimate disposal.

It is worth noting that quantifying carbon emissions also calls for an evolving view. For instance, when autonomous-driving cars increase, power consumption and vehicle weight will also increase, leading to less fuel efficiency.

This piece is intended as a wake-up call. The auto industry really needs to pay greater attention to transport decarbonization and to reclaim their commitment to a green economy. We suggest auto manufacturers take immediate actions, first by identifying industry activities that emit the most CO2 and then by objectively assessing and quantifying their own carbon footprints before coming up with any comprehensive CO2 reduction plans. Whosoever does this first will win themselves first-mover advantages in the competition towards a greener economy.

Life Sciences and Healthcare

Encouraging greater innovation in China’s pharmaceutical companies

China's pharmaceutical industry is becoming more innovative thanks to the government’s radical policy initiatives that were begun in 2019. The reform of drug policies and regulations has seen a whole range of breakthroughs in drug manufacturing as well as upgrades in China's pharmaceutical sector. During the 2021 "Two Sessions" meetings, the government emphasized the concept of "innovation to drive forward the development of the modern industrial structure”. Hence, we are likely to see a plethora of strategies to foster innovation and the development of more novel products in China's pharmaceutical industry.

The reform of pharma-related policies and regulations - "green channels" for new drug approval, new pathways for novel drugs.

China's generics and biosimilar market has been shrinking rapidly ever since a volume-based procurement (VBP) program was implemented by the government in 2019. This accelerated the transformation of Chinese pharma companies, re-focussing their efforts from catching up quickly to being the best-in-class and then first-in-class.  In 2020, the Chinese drug control agencies released a series of new directives and policies while at the same time modifying and updating existing regulations. Drug regulation agencies such as the National Medical Products Administration (NMPA) and the Center for Drug Evaluation (CDE), which covers various topics, including clinical trials, new drug approval process, pricing, reimbursement and so on were all involved in this effort which has transformed the structure of the pharmaceutical industry, steering it towards producing more innovative drugs.

The rise of domestic pharmas –the capacity to innovate is no longer the exclusive territory of MNCs

With the changes in government policy, domestic pharma companies have increased their capacity to develop and produce new drugs. According to PharmaProjects, China is one of the very few countries with an increase in the number of pharmaceutical R&D centers from 2019 to January 2021 (Figure 1), which highlights the rising investment in novel drug development in China.

Figure 1: Distribution of Pharma R&D companies by HQ country/region, 2019 to January 2021

Source: PharmaProjects, Pharma R&D Annual Review 2021

Furthermore, the distribution of newly approved novel drugs each year among domestic pharmas and MNCs is also shifting (Figure 2). In 2020, among all 48 newly approved novel drugs, there are 23 products from domestic pharmas and 25 from MNCs, basically a 50-50 split. As of May, 2021, however, there were already 9 products from domestic pharmas and 7 from MNCs.

Figure 2: The number of newly approved novel drugs in China, 2018 to May 2021

Source: Pharmacube, Deloitte Research

Pharmaceutical capital market – a boom in M&A deals

Another significant development in the pharmaceutical landscape is the increase in the number and value of M&A deals in China’s pharmaceutical market. This has been continuously on the rise for the last two years. According to Mergermarkets, a total of 97 deals were transacted in 2020, with total deal value breaking through the RMB 100 billion barrier (Figure 3). This increase in both deal number and value when compared to 2019 is mainly due to two reasons: the quick recovery from the pandemic in China; and the market response to the increasingly strong stream of innovations and breakthroughs in new drug production. In order to bolster R&D efforts and innovation many pharmaceutical companies are seeking to integrate, make strategic investments with other companies and/or go public via M&As.

Figure 3: China pharmaceutical market M&A deals in number and value. 2010 to May 2021

Source: Mergermarket, Deloitte Research

Challenges ahead – strengthening the basics while expanding actively

China has now entered the global pharmaceutical innovation capability tier-two country list thanks to the rapid development of R&D capabilities over the past few years. However, there is still a long way to go before China can become a tier-one pharmaceutical country. Three main challenges are likely to crop up along the way:

  • Enhancement in basic research: China is currently facing the problem of non-original innovation and a lack of original innovations. This is mainly due to domestic pharmas’ desire to catch up quickly with MNCs in terms of profitability. This makes them pay inadequate attention and allocate inadequate resources to basic research, resulting in an insufficient number of original products brought to the market by China’s pharmaceutical industry.
  • Improvement in research-to-business strategies: Many research projects with a high potential to go commercial have failed to launch in the market because no good research-to-business transformation strategy was in place. One important reason for this is that China’s pharmaceutical market still lacks sufficient research-to-business strategists to support the business transformation of their research projects.
  • Cultivation of talents: As a highly technology-oriented industry, China’s pharmaceutical industry still lacks of first-class talents in innovation development. Hence, it is important to get more overseas talent to return to China, as well as to cultivate young professionals in China who are not afraid of innovating. 

In sum, it is important to take good care of the foundation while aggressively increasing the capacity to innovate. But China's pharmaceutical industry can only grow faster and foster greater innovation with strong support from the government and capital markets, as well as a solid foundation in basic research and talent cultivation.



[2] Goldman Sachs Global Investment Research, 2019. New era in CO2 regulation

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