Speech by Jean-Claude Trichet, President of the ECB, Rheinisch-Westfälische Technische Hochschule (RWTH), It is a pleasure for me to be here in Aachen, a city that has played such a central role in the project of European integration.
As students at RWTH Aachen, you must be proud to be part of one of Europe’s leading institutions for science and research. This university has an international reputation, demonstrated both by its participation in global networks of higher education and by the presence of a large contingent of students from around the world. A degree from such a renowned university is indeed a great asset and a remarkable insurance against the uncertainties of your working lives.
In pursuing your studies, you have already had to make important decisions under uncertainty. Your choices of university and degree course were made with limited information – about the chances of obtaining the degree, about the impact of your degree on future job opportunities and about its relative merits compared with alternatives. Such uncertainty is a constant feature of our lives, as we experience the structural transformation of our economies driven by new technologies and globalisation.
Fifty years ago, future career paths were clear for most graduates. Engineering students would become engineers and medical students would become doctors. Nowadays all professions change at much greater speed. Engineers and doctors work side-by-side in such areas as nanotechnology and biomedical engineering. Many of you will be not so much filling existing jobs as inventing whole new jobs.
At the same time, increasing interactions between people and organisations across geographical borders makes it more difficult to appreciate the potential impact of economic developments elsewhere in the world on the prospects for your home country. The process of globalisation has many positive consequences, such as the benefits of trade, financial market integration and the acceleration of global growth. But there are risks too, such as the accumulation of so-called ‘global imbalances’, which were a key underlying cause of the global crisis.
All of you will be aware of the difficulties that the world economy has experienced in recent years: the financial crisis that began in 2007 and led to the deepest recession since World War II. Devising appropriate policy responses to the crisis has been a challenge for central banks everywhere. Many decisions have had to be made under exceptionally uncertain conditions, sometimes with very limited information and in constantly changing circumstances.
Today I would like to discuss with you our recent experience of decision-making in an uncertain world. I will outline how the crisis developed and then describe how we at the European Central Bank (ECB) responded – the kinds of information we draw on, the tools we use and the principles on which we base our decisions. I will close with some brief reflections on dealing with uncertainty.
II. Uncertainty and the crisis
The origins of the crisis lay in changes in the economic and financial environment over the past two decades. During that time, there was a marked decline in the volatility of such aggregate economic indicators as total household consumption and total business production. This led to a widespread perception that we were living in very benign economic conditions.
At the same time, some developed countries underwent a process of financial deregulation and innovation aimed at improving efficiency. New financial products were developed with the promise of enabling financial institutions to manage the risks in their lending activities more effectively. As a result, larger segments of the population obtained mortgage financing, and credit generally was more easily available.
But the promised benefits of financial risk management turned out to be illusory. Risk did not disappear, indeed in many cases it was magnified. And the process of deregulation led to a huge increase in private indebtedness and an accumulation of financial imbalances.
At the global level, a number of developed economies were able to finance increased household consumption by borrowing from fast-growing emerging economies that had an abundance of savings. These sustained global imbalances contributed to lower interest rates, which further encouraged the process of credit creation in countries that were receiving capital inflows.
It was clear to many careful observers that this process eventually should come to a halt. With the considerable benefit of hindsight, warning signals of the subsequent financial distress in the data for 2006-07 are clearly evident. In the name of my colleague central bankers, I gave myself a clear warning in January 2007 on the likelihood of a major market correction due to a significant under-assessment and under-pricing of risks in the financial markets. But the specifics of how a crisis might be triggered and the course of its subsequent propagation proved hard to predict in real time.
Ultimately, the crisis was ignited in August 2007 by unprecedented tensions in the interbank market, in which financial institutions lend to and borrow from one another. Following the bankruptcy of Lehman Brothers in September 2008, the financial market tensions developed into a loss of confidence across the whole economy and eventually a deep recession. After years of benign economic developments, all policy-makers suddenly faced very uncertain circumstances.
A key feature of the uncertainty generated by financial crises is that it places decision-makers in uncharted territory. Events happen that were deemed to be almost impossible before the crisis, and were therefore difficult to forecast on the basis of statistical methods.
This was the case for developments in the interbank market in the first phase of the crisis. Up until July 2007, the general perception among market participants was that loans between financial institutions were essentially safe. Banks trusted each other, both because bank defaults in developed economies had previously been rare events and because the very short loan periods minimised the risks that borrowers would not repay their loans.
As a result, banks were happy to lend to other banks in large amounts at the same interest rate that they were charged when borrowing from the central bank. Occasional differences of a few hundredths of a percentage point between these interest rates were interpreted as signs of stress, but they were often due to technical factors and therefore very short-lived.
But in August 2007, in response to negative developments in the market for US sub-prime mortgages, uncertainty about the creditworthiness of many financial institutions suddenly increased. Banks became unwilling to lend in the money market. As funds disappeared from the market, the difference between the cost of unsecured short-term funding from other banks – what in the euro area is called EURIBOR – and the interest rate on money provided by central banks suddenly jumped from near zero to unprecedented levels of around 60 basis points.
This sudden widening in the interest rate differential – what is known as the spread – happened simultaneously in the euro area, the US and the UK (see Figure 1). Not only was this unpredictable, but policy-makers and market participants were also extremely uncertain about whether the spread would widen further and when there would be a return to normal conditions.
Some researchers have drawn a parallel between the money market crisis and Nassim Taleb’s  description of ‘black swan’ events. The idea of black swan events originates from the assumption, based on centuries of experience in Europe, that there was only one kind of swan: white swans. This assumption was invalidated only in the eighteenth century by the observation of a black swan in Australia.
In Taleb’s analogy, ‘black swans’ are extreme outcome but low probability and highly unpredictable events. The parallel arises as the opening up of interbank market spreads in August 2007 could not be predicted based on historical data, because it was a low probability event. It became predictable – and justifiable – only with hindsight.
What happened next was that tensions remained high for a protracted period. In September 2008, spreads increased much further with the bankruptcy of Lehman Brothers. Economic uncertainty – as reflected, for example, in stock market volatility – rose dramatically.
The unpredictability of rare events highlights an important distinction between ‘risk’ and ‘uncertainty’, which was first made by the famous economist Frank Knight in 1921.
According to Knight, ‘risk’ refers to a situation of randomness where the range of possible events and the associated probability distribution are known. Risk therefore characterises situations such as the toss of a coin or weather forecasting. In both cases, we can characterise the set of possible outcomes and we can compute their likelihood.
‘Uncertainty’ refers instead to a situation where events cannot be enumerated and/or it is not possible to attach a probability to them. Events like the ‘black swan’ can more easily be characterised as uncertain, rather than risky. Since they have never been observed before, we do not know how to judge their likelihood.
III. Permanent alertness, judgement and experience
So how did central banks respond to the crisis?
I would like to highlight one simple principle: the timing of the policy response is crucially important. Financial crises can strike suddenly. The response to the crisis should be commensurably swift and decisive. This requires a stance of what I call permanent alertness, to identify promptly new threats to economic stability and price stability, including those arising from the crisis itself.
The decline in banks’ ability to raise funds on the interbank market led to a tightening of credit conditions facing households and businesses. There was a clear danger that this tightening would lead to a serious decline in economic activity, further credit losses and a vicious downward cycle of distress in financial markets and the real economy. When the crisis intensified in 2008, permanent alertness led to a resolute sequence of actions using the ECB’s standard policy tool, the short-term nominal interest rate.
But the crisis also demonstrated that deeper market failures in the financial sector might mean that standard policy responses alone prove insufficient to restore economic stability and price stability. Identifying these market failures and introducing measures to address them was a second dimension of the ECB’s policy response. This led to the introduction of a variety of what we call ‘non-standard’ measures to complement the reduction of policy interest rates.
Permanent alertness is my lesson on how to deal with the unpredictability of events. But alertness per se may suggest that we should simply be ready to adopt a specific, known reaction, once we observe a certain, possibly unpredictable, event. The problem in situations of “Knightian” uncertainty is that we are also uncertain in our assessment of the overall consequences of the unpredictable event and how we respond to it.
Let me again illustrate this point with an example. Once the crisis intensified in September 2008, central banks faced the major new difficulty of assessing how the combination of this exceptional event and of the unprecedented response of policy authorities would affect the medium-term outlook. We normally employ various statistical tools to help make this assessment, but would these tools provide useful guidance at this particular time?
Figure 2 provides an answer showing the evolution of our projections for annual economic growth in the euro area in 2009 together with the corresponding forecasts from a range of private sector and international organisations. Observations correspond to forecasts for GDP growth in 2009 made at different points. Over the months, information is updated and the forecast horizon becomes shorter and shorter. At the end of 2009, forecasting GDP growth in 2009 is almost tantamount to forecasting the past, so forecasts converge to the actual value indicated by a constant red line.
In 2008, all projections were strongly lagging actual developments. Only at the end of the year did public and private institutions begin to make downward adjustments to their growth forecasts for 2009, while nonetheless clearly underestimating the actual developments.
There is a similar pattern in Figure 3, which shows the forecasts for 2010 produced during the period 2009-10. In this case, forecasts systematically underestimated the strength of the recovery. In 2009, most forecasters expected very slow growth in 2010. As more positive news emerged in the second half of 2009, the forecasts were steadily revised upwards but still remained well short of the final outcome until the last quarter of the year.
The lagging nature of the information contained in most projections, together with the large projection errors, highlight the relative inadequacy of standard tools to deliver accurate forecasts during times of heightened economic distress.
What can guide a decision-maker in such circumstances?
A well-known recommendation of control theory is to apply robust control. This is designed to achieve robust performance in the presence of potential modelling errors. One approach will deliver the best possible outcome in the worst case scenario. This strategy is used widely in engineering applications, and it has the advantage of avoiding nasty surprises.
But the strategy also has disadvantages, should the worst case scenario be too extreme or highly unlikely. For example, if students think that the worst case scenario is that they will never find a job after gaining a degree, they may act accordingly and immediately abandon their studies. But that choice would be very far from ideal in the event that jobs are indeed available for graduates.
In very uncertain circumstances, judgement and experience may be the safest bets for a policy-maker. To illustrate this point, I like to draw a comparison to chess.
Over several decades, psychologists have explored how chess grandmasters obtain their advantage over lesser players. The evidence indicates that grandmasters rely significantly on a vast store of carefully structured knowledge of game positions, which has been accumulated over many years. So their advantage is not necessarily due to innate superior mental computation ability, but rather the stock of knowledge built up from countless hours of practical experience.
Monetary policy is not chess. Nevertheless, knowledge and experience are always useful in complementing a strong analytical exploration of the possible decisions. When dealing with a very high degree of uncertainty the analytical work might be less reliable and experience appears to be playing a more important role in the decision-making process. The occurrences of such very uncertain situations are also an additional reason for central banks to rely upon what I call “collegial wisdom”. From different vantage points we could take stock of our knowledge of the sovereign debt crisis of the emerging countries in the 1980s, of the crisis of the European monetary system in 1992 and 1993 of the Mexican and Asian crisis of the 1990s and the dotcom bubble burst in the 2000s. Pooling experiences of members of the members of the Executive Board and the Governing Council of the ECB proved extremely important in the circumstances.
Let me sum up my three simple lessons for dealing with highly uncertain circumstances: first, remain permanently alert and ready to respond to change when it happens; second, always ask the analytical preparation to be as comprehensive and robust as possible; and third, do not forget that in such circumstances collegial wisdom and experience are always of the essence.
I am of course fully aware that my three lessons are not a straightforward solution to life’s uncertainties. Nor are they contingent mathematical laws that you can apply when you see fit. As the great physicist and Nobel laureate Richard Feynman once said “Imagine how much harder physics would be if electrons had feelings!”
Monetary policy-making – and life – would certainly be much simpler, but also much duller, if as in physics a few basic laws could explain most experiences.
Thank you for your attention – and may I wish you well in your studies and in your future when making decisions in an uncertain world.
Kenny, G. and J. Morgan (2011), ‘Some Lessons from the Financial Crisis for the Economic Analysis’, unpublished manuscript, European Central Bank.
Knight F. (1921) ‘ Risk, Uncertainty, and Profit,’ Boston, MA: Hart, Schaffner & Marx; Houghton Mifflin Company.
Taleb N. (2007), ‘The Black Swan: The Impact of the Highly Improbable’, Random House.
Taylor J. and J.C. Williams (2009), ‘A Black Swan in the Money Market’, American Economic Journal: Macroeconomics, 1(1), pp. 58-83.
 John Taylor and John Williams (2011) and Nassim Taleb (2007).
Copyright © for the entire content of this website: European Central Bank, Frankfurt am Main, Germany.
Lockdown 2.0 – Here’s how to be the best-looking person in the virtual room
suggests “the product you’re creating is not the camera, the lens or a webcam’s clever industrial design. It’s the subject, you, which is just on e part of the entire image they see. You want that image to convey quality, not convenience.”
Technology experts at Reincubate saw an opportunity in the rise of remote-working video calls and developed the app, Camo, to improve the video quality of our webcam calls. As part of this, they consulted the digital photography expert and author, Jeff Carlson, to reveal how we can look our best online.
It’s clear by now that COVID-19 has normalised remote working, but as part of this the importance of video calls has risen exponentially. While we’re all used to seeing the more casual sides of our colleagues (t-shirt and shorts, anyone?), poor webcam quality is slightly less forgivable.
But how can we improve how we look on video? We consulted Jeff Carlson for some top tips– here is what he had to say.
- Improve the picture quality of your call
The better your camera, the higher quality your webcam calls will be. Most webcams (as well as currently being hard to get hold of and expensive), are subpar. A DSLR setup will give you the best picture, but will cost $1,500+. You can also use your iPhone’s amazing camera as a webcam, using the new app from Reincubate, Camo.
Jeff’s comments “The iPhone’s camera system features dedicated coprocessors for evaluating and adjusting the image in real time. Apple has put a tremendous amount of work into its imaging software as a way to compensate for the necessarily small camera sensors. Although it all works in service of creating stills and video, you get the same benefits when using the iPhone as a webcam.”
Aidan Fitzpatrick, CEO of Reincubate explains why the team created Camo, “Earlier this year our team moved to working remotely, and in video calls everyone looked pretty bad, irrespective of whether they were on built-in Mac webcams or third-party ones. Thus began my journey to build Camo: an iPhone has one of the world’s best cameras in it, so could we make it work as a webcam? Category-leading webcams are noticeably worse than an iPhone 7. This makes sense: six weeks of Apple’s R&D spend tops Logitech’s annual gross revenue.”
- Place your camera at eye level
A video call will never quite be the same as a face-to-face conversation, but bringing your camera up to eye level is a good place to start. That can involve putting your laptop on a stand or pile of books, mounting a webcam to the top of your display screen, or even using a tripod to get the perfect position.
Jeff points out, “If the camera is looking down on you, you’ll appear minimized in the frame; if it’s looking up, you’re inviting people to focus on your chin, neck, or nostrils. Most important, positioning the camera off your eye level is a distraction. Look them in the eye, even if they’re miles or continents away.”
Low camera placement from a MacBook
- Make the most of natural lighting
Be aware of the lighting in the room and move yourself to face natural lighting if you can. Positioning the camera so any natural light is behind you takes the light away from your face, which can make it harder to see and read expressions on a call.
Jeff Carlson’s top tip: “If the light from outside is too harsh, diffuse it and create softer shadows by tacking up a white sheet or a stand-alone diffuser over the window.”
Backlit against a window Facing natural light
- Use supplementary lighting like ring lights
The downside to natural lighting is that you’re at the mercy of the elements: if it’s too bright you’ll have the sun in your eyes, if it’s too dark you won’t be well lit.
Jeff recommends adding supplementary lighting if you’re looking to really enhance your video calls. After all, it looks like remote working will be carrying on for quite some time.
“The light can be just as easy as a household or inexpensive work light. Angle the light so it’s bouncing off a wall or the ceiling, depending on your work area, which, again, diffuses the light and makes it more flattering.
Or, for a little money, use a softbox or a shoot-through umbrella with daylight bulbs (5500K temperature), or if space is tight, LED panels. Larger lights are better for distributing illumination– don’t be afraid to get them in close to you. Placement depends on the look you’re going after; start by positioning one at a 45-degree angle in front and to the side of you, which lights most of your face while retaining nice shadow detail.”
In some cases, a ring light may work best. LEDs are arranged in a circle, with space in the middle to put the camera’s lens and get direct illumination from the direction of the camera.
- Centre yourself in the frame
Make sure you’re getting the right angle and that you’re using the frame effectively.
“You should aim for people to see your head and part of your torso, not all the space between your hair and the ceiling. Leave a little space above your head so it’s not cut off, but not enough that someone’s eyes are going to drift there.”
- Be mindful of your backdrop
It’s not always easy to get the quiet space needed for video calls when working from home, but try as best you can to remove anything too distracting from your background.
“Get rid of clutter or anything that’s distracting or unprofessional, because you can bet that will be the second thing the viewers notice after they see you. (The Twitter account @RateMySkypeRoom is an amusing ongoing commentary on the environments people on television are connecting from.)”
A busy background as seen by a webcam
- Make the most of virtual backgrounds
If you’re really struggling with finding a background that looks professional, try using a virtual background.
Jeff suggests: “Some apps can identify your presence in the scene and create a live mask that enables you to use an entirely different image to cover the background. While it’s a fun feature, the quality of the masking is still rudimentary, even with a green screen background that makes this sort of keying more accurate.”
- Be aware of your audio settings
Our laptop webcams, cameras, and mobile phones all include microphones, but if it’s at all possible, use a separate microphone instead.
“That can be an inexpensive lavalier mic, a USB microphone, or a set of iPhone earbuds. You can also get wireless lavalier models if you’re moving around during a call, such as presenting at a whiteboard in the camera’s field of view.
The idea is to get the microphone closer to your mouth so it’s recording what you say, not other sounds or echoes in the room. If you type during meetings, mount the mic on an arm instead of resting it on the same surface as your keyboard.”
- Be wary of video app add-ons
Video apps like Zoom include a ‘Touch up your appearance’ option in the Video settings. This applies a skin-smoothing filter to your face, but more often than not, the end result looks artificially blurry instead of smooth.
“Zoom also includes settings for suppressing persistent and intermittent background noise, and echo cancellation. They’re all set to Auto by default, but you can choose how aggressive or not the feature is.”
- Be the best looking person in the virtual room
What’s important to remember about video calls at this point in time is that most people are new to what is, really, personal broadcasting. That means you can easily get an edge, just by adopting a few suggestions in this article. When your video and audio quality improves, people will take notice.
Bringing finance into the 21st Century – How COVID and collaboration are catalysing digital transformation
By Keith Phillips, CEO of TISATech
If just six or seven months ago someone had told you that in a matter of weeks people around the world would be locked down in their homes, trying to navigate modern work systems from a prehistoric laptop, bickering with family over who’s hogging the Wi-Fi, migrating online to manage all financial services digitally, all while washing their hands every five minutes in fear of a global pandemic… You’d think they had lost their mind. But this very quickly became the reality for huge swathes of the world and we’re about to go through that all over again as the UK government has asked that those who can work from home should.
Unsurprisingly, statistics show that lockdown restrictions introduced by the UK government in March, led to a sharp increase in people adopting digital services. Banks encouraged its customers to log onto online banking, as they limited (and eventually halted) services at branches. This forced many customers online as their primary means of managing personal finances for the first time.
If anyone had doubts before, the Covid-19 pandemic proved to us the importance of well-functioning, effective digital financial services platforms, for both financial institutions and the people using them.
But with this sudden mass online migration, it’s become clear that traditional banks have struggled to keep up with servicing clients virtually. Legacy banking systems have always stilted the digitisation of financial services, but the pandemic thrust this issue into the limelight. Fintech firms, which focus intently on digital and mobile services, knew it was only a matter of time before financial institutions’ reliance was to increase at an unprecedented rate.
For years, fintechs have been called upon by traditional players to find solutions to problems borne from those clunky legacy systems, like manual completion of account changes and money transfers. Now it is the demand for these services to be online coupled with the need for financial services firms to cut costs, since Covid-19 hit the economy.
Covid-19 has catalysed the urgent need to bring digital transformation to a wider pool of financial services businesses. Customers now have even higher expectations of larger institutions, demanding that they keep up with what the younger and more nimble challengers have to offer. Industry leaders realise that they must transform their businesses as soon as possible, by streamlining and digitising operations to compete and, ultimately, improve services for their customers.
The race for digital acceleration began far before the recent pandemic – in fact, following the 2008 financial crisis is likely more accurate. Since the credit crunch, there has been a wave of new fintech firms, full of young, bright techies looking to be the next big thing. Fintechs have marketed themselves hard at big conferences and expos or by hosting ‘hackathons’, trying to prove themselves as the fastest, most innovative or the most vital to the future of the industry.
However, even during this period where accelerating innovation in online financial services and legacy systems is crucial, the conditions brought about by the pandemic have not been conducive to this much-needed transformation.
The second issue, which again was clear far before the pandemic, is that fact that no matter how nimble or clever the fintechs’ solutions are, it is still hard to implement the solutions seamlessly, as the sector is highly fragmented with banks using extremely outdated systems populated with vast amounts of data.
With the significance of the pandemic becoming more and more clear, and the need for better digital products and services becoming more crucial to financial services firms and consumers by the day, the industry has finally come together to provide a solution.
The TISAtech project was launched last month by The Investing and Saving Alliance (TISA), a membership organisation in the UK with more than 200 leading financial institutions as members. TISA asked The Disruption House, a specialist benchmarking and data analytics business, to create a clearing house platform for the industry to help it more effectively integrate new financial technology. The project aims to enhance products and services while reducing friction and ultimately lowering costs which are passed on to the customers.
With nearly 4,000 fintechs from around the world participating, it will be the world’s largest marketplace dedicated to Open Finance, Savings, and Investment.
Not only will it provide a ‘matchmaking’ service between financial institutions an fintechs, it will also host a sandbox environment. Financial institutions can pose real problems with real data and the fintechs are given the space to race to the bottom – to find the most constructive, cost-effective solution.
Yes, there are other marketplaces, but they all seem to struggle to achieve a return on investment. There is a genuine need for the ‘Trivago’ of financial technology – a one stop shop, run by an independent body, which can do more than just matchmaking. It needs to go above and beyond to encompass the sandboxing, assessments, profiling of fintechs to separate the wheat from the chaff, and provide a space for true collaboration.
The pandemic has taught us that we are more effective if we work together. We need mass support and collaboration to find solutions to problems. Businesses and industries are no different. If fintechs and financial institutions can work together, there is a real chance that we can start to lessen the economic hit for many businesses and consumers by lowering costs and streamlining better services and products. And even if it is just making it that little bit easier to manage personal finances from home when fighting with your children for the Wi-Fi, we are making a difference.
What to Know Before You Expand Across Borders
By Sean King, Director of International Tax at McGuire Sponsel
The American retail giant, Target Corporation, has a market cap of $64 billion and access to seemingly limitless resources and advisors. So, when the company engaged in its first global expansion, how could anything possibly go wrong?
Less than two years after opening its first Canadian store in 2013, Target shut down all133 Canadian locations and terminated more than 17,000 Canadian employees.
Expansion of an operation to another country can create unique challenges that may impact the financial viability of the entire enterprise. If Target Corporation can colossally fail in its expansion to Canada, how might Mom ‘N’ Pop LLC fare when expanding into Switzerland, Singapore, or Australia?
Successful global expansion requires an understanding of multilayered taxes, regulatory hurdles, employment laws, and cultural nuances. Fortunately, with the right guidance, global expansion can be both possible and profitable for businesses of any size.
Any company with global ambitions must first consider whether the company’s expansion outside of the U.S. will give rise to a taxable presence in the local country. In the cross-border context, a “permanent establishment” can be created in a local country when the enterprise reaches a certain level of activity, which is problematic because it exposes the U.S. multinational to taxation in the foreign country.
Foreign entity incorporation
To avoid permanent establishment risk, many U.S. multinationals choose to operate overseas through a formal corporate subsidiary, which reduces the company’s foreign income tax exposure, though it may result in an additional level of foreign income tax on the subsidiary’s earnings. In most jurisdictions, multinationals can operate their business in the foreign country as a branch, a pass through (e.g., partnership,) or a corporation.
As a branch, the U.S. multinational does not create a subsidiary in the foreign country. It holds assets, employees, and bank accounts under its own name. With a pass through, the U.S. multinational creates a separate entity in the foreign country that is treated as a partnership under the tax law of the foreign country but not necessarily as a partnership under U.S. tax law.
U.S. multinationals can also create corporate subsidiaries in the foreign country treated as corporations under the tax law of both the foreign country and the U.S., with possibly two levels of income taxation in the foreign country plus U.S. income taxation of earnings repatriated to the U.S. as dividends.
Under U.S. entity classification rules, certain types of entities can “check the box” to elect their classification to be taxed as a corporation with two levels of tax, a partnership with pass-through taxation, or even be disregarded for U.S. federal income tax purposes. The check the box election allows U.S. multinationals to engage in more effective global tax planning.
Toll charges, transfer pricing and treaties
When establishing a foreign corporate subsidiary, the U.S. multinational will likely need to transfer certain assets to the new entity to make it fully operational. However, in many cases, the U.S. multinational cannot perform the transfer without recognizing taxable income. In the international context, the IRS imposes certain outbound “toll charges” on the transfer of appreciated property to a foreign entity, which are usually provided for in IRC Section 367 and subject to various exceptions and nuances.
Instead, the U.S. multinational may prefer to license intellectual property to the foreign subsidiary for a fee rather than transfer the property outright. However, licensing requires the company and foreign subsidiary to adhere to transfer pricing rules, as dictated by IRC Section 482. The U.S. multinational and the foreign subsidiary must interact in an arms-length manner regarding pricing and economic terms. Furthermore, any such arrangement may attract withholding taxes when royalties are paid across a border.
Are you GILTI?
Certain U.S. multinationals opt to focus on deferring the income recognition at the U.S. level. In doing so, they simply leave overseas profits overseas and delay repatriating any of the earnings to the U.S.
Despite the general merits of this form of planning, U.S. multinationals will be subject to certain IRS anti-deferral mechanisms, commonly known as “Subpart F” and GILTI. Essentially, U.S. shareholders of certain foreign corporations are forced to recognize their pro rata share of certain types of income generated by these foreign entities at the time the income is earned instead of waiting until the foreign entity formally repatriates the income to the U.S.
The end goal
Essentially, all effective international tax planning boils down to treasury management. Effective and early tax planning can properly allow a company to better achieve its initial goal: profitability.
If global expansion is on the horizon for your company, consult a licensed professional for advice concerning your specific situation.
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