Transcript
Speaker: This is HSBC Global Viewpoint, your window into the thinking, trends and issues shaping global banking and markets.
Speaker: Join us as we hear from industry leaders and HSBC experts on the latest insights and opportunities for your business.
Speaker: Thank you for listening.
Speaker: You're listening to the HSBC Global Research Macro Viewpoint, our weekly review of the key reports from our team of economists and strategists across the globe.
Speaker: Coming up today, we look at two of the big stories dominating the financial headlines this week, the extreme pressure on China's property markets and the severe crunch in the global gas market that has caused prices to soar.
Speaker: And we also find out how machine learning techniques can be used to help predict export growth.
Speaker: This podcast was recorded on Thursday, the 23rd of September, 2021.
Speaker: Our full disclosures and disclaimers can be found in the link attached to this podcast.
Speaker: Hello, I'm Chris Brown-Hulmes.
Speaker: And I'm Aline Van Dyne.
Speaker: Issues surrounding Evergrande, China's second largest property developer, have been at the forefront of investors' minds this week.
Speaker: With China's property market slowing, concerns remain about the contagion risk to the broader sector and economy.
Speaker: So how could Beijing respond?
Speaker: Let's get the thoughts of Xu Hongbin, Chief China Economist.
Speaker: So Hongbing, first of all, can you give us a bit of background on the recent regulatory picture around China property?
Speaker: Sure.
Speaker: As we all know, China was first in first of all in terms of the pandemic lockdown.
Speaker: As a result, by the fourth quarter last year, GDP growth rate has already rebound to pre-pandemic level.
Speaker: So following that, the policymakers started to pay more attention to potential risk.
Speaker: So they found that actually the rapid rebound in the property price is one of the major risks.
Speaker: As a result, they're starting to impose tidal measures mainly on the financing front.
Speaker: For instance, they have the so-called three red lines.
Speaker: which literally means that for those highly-leverage property developers, there are very tough restrictions in terms of access to the funding.
Speaker: And then they expand a titling measure towards property-related loan limit for the commercial banks.
Speaker: And then the latest around, they also starting to impose some restrictions in the mortgage lending.
Speaker: So put all this together and we start to see accumulated effect of those tightening measures.
Speaker: And then the property sales start to come down, property investments also come down.
Speaker: And of course, we also see some rising signs for the liquidity stress for the property developers as well.
Speaker: Obviously, Evergrande is a name everyone's reading about in the headlines.
Speaker: Why them in particular?
Speaker: Well, I think partly because this is something specific for Evergrande because there's the most indebted property developer in China.
Speaker: And so obviously under this kind of macro policy tightening environment, they are the first ones to see the problem.
Speaker: But the key question is that we start to see the initial signs for a sector-wide kind of liquidity stress.
Speaker: And would it be fair to say that the property clampdown might have been a little stronger than expected?
Speaker: I think the answer is probably yes.
Speaker: If you look at all those tidying measures, none of them individually are strict enough to cause some kind of overtitling.
Speaker: But the problem is that if simultaneously you have those kind of tidying measures from all fronts, and then you end up with this kind of compounding effect, probably end up to be bigger than people expected.
Speaker: Contagion is an obvious concern here.
Speaker: What do you think are the wider implications for property banks and the broader economy?
Speaker: Sure.
Speaker: What we see here is that it's not just a slowdown in the property sales, it's also the rising liquidity stress for the whole sector.
Speaker: And given that property market accounts for around a quarter of the GDP, and also given that the banks is also heavily involved in terms of the property landings,
Speaker: Any kind of potential risk of contingent effect as a result of this kind of liquidity stress is going to have a kind of serious unintended consequence for the broader economy as well as the broader system.
Speaker: I think this is certainly quite understandable for market to worry about this.
Speaker: And also more importantly, I think the policymakers are aware of this potential contingent risk as well.
Speaker: So what do you think are the options for policymakers in terms of limiting the damage and containing further risk?
Speaker: Well, I think as we all know, the whole purpose of this property tightening is the leveraging and prevent systematic risk in the future.
Speaker: But at the same time, you don't want to create immediate crisis.
Speaker: As a result, I think given that we already see some initial signs for sector wide liquidity stress,
Speaker: I think that now is the time for policymakers to make some kind of fine tuning in terms of the leveraging process.
Speaker: In other words, we expect them firstly to ease the restrictions in terms of funding, particularly for the high-housing developers.
Speaker: And secondly, we also expect them to improve the efficiency in terms of mortgage improving process.
Speaker: And thirdly, I think it is a time for them also to build up some sort of fence or firewalls between the individual highly leveraged troubled property developers with the rest of the sector to prevent turnover effect from this kind of potential liquidity tightness.
Speaker: Hongbin, thanks very much.
Speaker: My pleasure.
Speaker: Let's turn to the gas market now where prices have hit record highs in Europe and Asia.
Speaker: Kim Fustier, oil and gas analyst, is here to explain what's behind this energy crisis.
Speaker: So, Kim, I guess the obvious question, why are natural gas prices soaring?
Speaker: There's actually a lot of different reasons for the current gas crunch.
Speaker: It's really a mix of supply and demand side issues.
Speaker: On the demand side, demand for gas and LNG has been really strong in Asia, not just in China, but other Asian countries as well.
Speaker: And that's just meant that Europe has had to compete for LNG cargoes on price with Asia.
Speaker: So prices in Europe and Asia have been chasing each other up.
Speaker: You've also had strong demand for gas in power generation in the UK and parts of Europe because of low wind speeds, low hydro or low nuclear.
Speaker: And on the supply side, there's been a long string of LNG outages around the world.
Speaker: We've also seen very steep declines in European gas production.
Speaker: For example, UK North Sea gas output is 25% lower than it was last year.
Speaker: And then, of course, there's the big one, which is that Russian gas exports to Western Europe have been below expectations.
Speaker: So one reading of the situation is that Russia has prioritized refilling its own storage after a cold winter.
Speaker: But there's also speculation that Russia is holding back supply to encourage Europe to approve the Nord Stream 2 pipeline.
Speaker: Do you think these are temporary factors or are they going to last a while?
Speaker: I think some of those factors won't be resolved anytime soon.
Speaker: There's very little new gas supply coming on in the next few months.
Speaker: For instance, Nord Stream 2 looks like it's only going to start up in the first quarter of 2022.
Speaker: Previously, we were hoping for that pipeline to start at the end of this year.
Speaker: So some of the LNG supply outages will get resolved, hopefully.
Speaker: So we will get a bit more gas in winter.
Speaker: Then again, gas demand in winter for heating in particular goes up very sharply.
Speaker: So something will have to be done on the demand side as well to curb demand.
Speaker: And this is where pricing comes in.
Speaker: We think gas prices will have to be high enough in order to encourage gas to coal or gas to oil switching in the power sector.
Speaker: And if that doesn't happen, obviously, we'll have, you know, we'll have supply issues, we might have shortages in some countries, particularly if we have a very cold winter, and we have we could have risks of very severe price spikes even higher than where prices are today.
Speaker: Yeah, what does happen if the northern hemisphere gets a really cold winter?
Speaker: I think the risk is that we run into extremely low inventory levels, particularly in Europe.
Speaker: So inventories were depleted already after a cold winter, 20 to 21.
Speaker: And we're now going into winter with already depleted inventories.
Speaker: So like I said, the risk is that there could be gas shortages in some countries, and that would force Europe to compete on price for LNG with Asia, and that would send prices soaring even higher than where prices are today.
Speaker: So final question, Kim, it seems a bit ironic that we're trying to reduce our dependence on fossil fuels and yet we end up in a situation like this.
Speaker: Yes, indeed.
Speaker: I think the response to this is going to be interesting because some people will be tempted to blame renewables and underinvestment in fossil fuels for the current crisis.
Speaker: And others will say on the contrary that we in Europe need to reduce our reliance on hydrocarbons.
Speaker: which seems completely contradictory.
Speaker: But it's the usual trilemma, I think, of trying to have cheap, clean and reliable energy at the same time.
Speaker: And it seems that that's not a problem that can be solved easily.
Speaker: So ultimately, we'll need more investment into all kinds of energy, whether that's gas, LNG, but also more gas storage, more renewables and more backup capacity.
Speaker: Kim, that's a great summary.
Speaker: Thank you very much for your time today.
Speaker: Thank you.
Speaker: This week, our trade economist, Shanela Rajanagam, joined up with our data science team to look at how machine learning can help predict export growth across the globe.
Speaker: She joins us now.
Speaker: So Shanela, tell us a bit more about the purpose of this analysis.
Speaker: Well, in this note, we use machine learning to carry out two key tasks.
Speaker: So the first is to determine what factors actually drive goods export growth in the medium term, and secondly, to forecast goods export growth after 2026 for 27 key economies.
Speaker: And the reason we decided to do this note is because trade has an important role to play in the economic recovery post-COVID.
Speaker: And indeed, we're already seeing that global trade volumes are well above what they were pre-pandemic.
Speaker: Why have you used machine learning for these tasks?
Speaker: So machine learning models are generally better at learning more complex relationships than traditional approaches.
Speaker: They're also a little bit more powerful.
Speaker: And specifically, this analysis uses tree-based machine learning techniques.
Speaker: So our data science team built two models for this analysis.
Speaker: A contemporaneous model that firstly allows us to determine the key drivers of export growth.
Speaker: But it also enables us to compare our predictions against actual export growth.
Speaker: And this allows us to see whether there might be other factors outside our model, for example, Brexit or changing weather patterns that could influence export growth going forward.
Speaker: They then use the important drivers of export growth as a starting point to build a predictive model to do the forecasting out to 2026.
Speaker: And so far, you know, studies like this that apply machine learning techniques to international trade have actually been fairly limited.
Speaker: So we also thought that this would be a relatively novel way to test the techniques.
Speaker: So what do the models show us about the key drivers of exports?
Speaker: Well, reassuringly, it is largely as you would expect.
Speaker: So our analysis found that medium term goods export growth is best explained by shorter term goods export growth.
Speaker: And this suggests that expanding exports can deliver long lasting benefits, for example, via improved competitiveness or increased foreign investment that may help economies continue to boost exports in the future.
Speaker: The model also found that imports of goods and services trade are important for increasing goods exports.
Speaker: And this aligns with what we know about how supply chains work.
Speaker: And the model also highlighted that reducing trade barriers, for example, import tariffs and regulatory restrictions can also help to lift goods exports.
Speaker: And turning to the goods export growth forecasts, what are your conclusions?
Speaker: So in this note, we forecast average annual nominal goods export growth over the period 2021 to 2026.
Speaker: And within the 27 economies we looked at, Vietnam, Bangladesh, Sri Lanka, the Philippines and Mexico are expected to experience the fastest growth in goods exports.
Speaker: And this is likely to be supported by trade liberalisation.
Speaker: And many of these economies are involved in new trade deals, but also low labour costs and the ongoing reconfiguration of supply chains.
Speaker: Shanela, thanks very much.
Speaker: Thanks for having me.
Speaker: So that's it for today's programme.
Speaker: Thank you to our guests, Xu Hongbin, Kim Fustia and Shanela Rajanayagam.
Speaker: From all of us on the team, thanks for listening.
Speaker: Please join us next week for another edition of The Macro Viewpoint.
Speaker: Thank you for listening today.
Speaker: This has been HSBC Global Viewpoint, Banking and Markets.
Speaker: For more information about anything you heard in this podcast or to learn about HSBC's global services and offerings, please visit gbm.hsbc.com.
