Joseph Shupac

Valuing Italy

The results of the 2018 election in Italy reflected two main economic realities: the economic struggles in Italy relative to northern Europe, and the economic struggles in southern Italy relative to northern Italy. The former helped anti-establishment parties to gain a large share of the country’s vote. The latter resulted in Lega Nord and centre-right parties performing well throughout much of the north of Italy, and the 5-Star Movement performing well in the south of Italy.

In geopolitics, the school of thought that argues that geography is the most significant or fundamental element in politics, these two economic realities have the same obvious source: mountains. Italy and southern Europe are much more mountainous than northern Europe, and southern Italy is much more mountainous than northern Italy. Mountainous regions tend to be much poorer than non-mountainous regions. Italy is no exception.

The question most analysts are now asking is what the broader consequences of Italian politics will be. On the one hand, Italy is too big for Europe to bully. On the other hand, Italy is too big for Europe to ignore. I do not have any insight as to how one might succeed or fail at predicting the short-to-medium term financial outcomes of this political situation.

A question that analysts are not asking, though, is whether the geographic realities that are underpinning current Italian and European economics may change as a result of technological developments. To put it directly, will modern technology — the Internet, automation, etc.– alter the economic disparity between mountainous and non-mountainous areas?

If they were to do so, Italy would be in a far more advantageous position than it is today. Its internal economic disparities between north and south would shrink, while at the same it would likely be able to capitalize on its central position within the mountainous Mediterranean region. Its entire territory of 301,000 square km (84 percent as large as Germany’s, but with much greater proximity to the sea) and population of 61 million (74 percent as large as Germany’s) would suggest that Italy’s GDP might not, in the long run, remain as small (53 percent as large as Germany’s) as it is today. For this reason, if current politics cause Italian markets to turn negative, then long-term investment opportunities in Italy may grow.

So, will new technologies help the economies of mountainous areas to catch up with those of non-mountainous economies?

My suspicion is that they will. Companies like Google are now trying to develop technologies that will allow cheap, high-speed Internet to become accessible even in rural and mountainous areas. Logically, it seems plausible that mountainous areas would benefit from high-speed Internet more than non-mountainous areas, as the benefits of virtual accessibility may be more significant in areas where real, physical accessibility is low.

Automation may have a similar impact. If autonomous logistics facilities (warehousing, loading and unloading vehicles) allow for efficient intermodal cargo transportation, it could benefit geographies like Italy by making it easier to transfer goods between ships, railways, or large trucks (which do not operate well or at all in most mountainous areas) and small trucks (which do operate relatively well in mountainous areas, but are generally not efficient elsewhere).

And if transport vehicles themselves become autonomous, it could greatly increase the efficiency of using trucks, and particularly small trucks, and particularly small trucks operating in mountainous areas where speed limits are lower and safety risks are higher, as the labour costs involved in (especially small) trucking are far higher than in rail or sea transport.

In my view, the question of mountainous relative to non-mountainous areas may be the key long-term question in determining the north-south balance in Europe (just as the question of coastal relative to continental areas may be the key long-term question determining the east-west balance in Europe). Non-mountainous areas have performed extremely well economically during the past two centuries, presumably as a result of the spread of canals, railways, and highways, all of which are much better suited to flat landscapes than to mountainous ones.

But we should not assume that flat areas will continue to so outperform mountainous ones going forward. We should try not to lose sight of this long term question; it may ultimately be easier to answer than the questions about what will happen to Italian and European politics and markets in the shorter term.

Devil’s Advocate: An unconventional, long-shot case for Elon Musk

I would not invest in Tesla. I think Elon Musk’s style is a little bit annoying, and I think many of his supporters are very annoying. More importantly I am not sold on the claim that Tesla will be able to compete against other auto or tech firms, even assuming that electric vehicles really do become widespread soon.

Looking at Musk’s business moves individually they appear, at best, to be high risk, high reward.

For example:

— Tesla’s approach to autonomous driving is not to use LIDAR, because LIDAR is expensive. This is unique: the other auto and tech firms are all betting on LIDAR. And because the economic viability of electric vehicles probably depends on autonomous driving (the vehicles need to be able to drive themselves to and from charging stations, as otherwise charging batteries may be too inconvenient when compared to conventional or hybrid vehicles), if this LIDAR-free strategy fails, it might put Tesla in a very tough position.

— Large electric trucks do not seem to make obvious economic sense: the batteries are too big, bulky, and expensive. It is difficult to see why these would be able to compete, in the short run, against conventional trucks, and in the long run against robots making it much easier to transfer cargo between electric railways and “first-mile/last-mile” conventional trucks or smaller electric trucks.

— Solar City. Even assuming that solar can compete with other power industries, and even assuming that using batteries to store power can compete with other forms of energy storage, it is difficult to see why a diffuse system of rooftop solar panels would be able to compete with solar farms, where installation and maintenance costs per panel are lower and where there is less shade.

–Boring company. Even assuming that Musk does succeed in reducing urban tunnelling costs, such tunnels would still be hugely expensive, so it is not clear why you would use them to move cars or people on `sleds`, when it would be much more efficient from a capacity point of view to simply use an existing technology within the tunnels: namely, trains.

The Unconventional, Long-Shot Case: Tesla Parking Lots

Readers of this blog will know I have a weird obsession with parking lots, because parking lots are the most ubiquitous type of American real estate and because they may be impacted more than other types by technologies like e-commerce and autonomous parking. Let’s imagine what Elon Musk might be able to do with a typical supersized suburban parking lot:

— No LIDAR, no liability, no problem: while autonomous vehicles in general might need LIDAR and might face liability issues, in a controlled, pedestrian-free environment — for example, in a designated autonomous zone of a parking lot — an autonomous car could function without LIDAR. This would have two benefits: one, it would act in effect as a valet service, making it easy to park; two, the parking lot could have an autonomous charging station for electric cars, so that your car could be charged while you are in the mall

— Sledding. The car-carrying ‘sleds’ imagined for use inside the Boring Company’s tunnels may not make economic sense within those tunnels, but they could make sense as sleds that could carry conventional, non-autonomous cars (there are hundreds of millions of these cars in America today, and they aren’t going to disappear overnight) to and from parking spots.

— The Boring Company. If the Boring Company ends up reducing the cost of conventional subway trains, the value of autonomous valet parking lots could increase, as people will drive their car to a parking lot at the nearest subway station, then get on the subway train while the car goes to park itself. (They may also be able to get in another car at their destination station’s parking lot, thus overcoming the ‘first-mile, last-mile challenge’ that plagues suburban transit in America today). Short-distance tunnels created by the Boring Company could also be used to link together parking lots that are close together: lots of suburban parking lots are giant ‘archipelagos’ separated by highways, for example.

— Electric Trucks. Electric trucks may not be economical in general, but could be economical in a specific situation: driving short ‘first-mile/last-mile’ distances, in daytime or overnight (electric vehicles are quiet, so better for nighttime use) between, for example, a commercial/industrial parking lot and a rail or conventional truck logistics station. So, for example, a company like Walmart could use electric trucks to bring in cargo quietly at night when its parking lot is empty, and also charge their batteries in the lot.

— Solar City. Rooftop solar panels may not be economically competitive in general, but on large flat roofs with little shade — notably, on large commercial/industrial roofs, next to large parking lots — they may be more economical. It may even become economical to put a solar roof above the large parking lots, to generate power while also helping to keep the parked cars shaded.

Okay, I admit, this is all unfounded, unclear, and far-fetched. Ultimately, it is based on the assumption that if wholly autonomous cars do not become widespread in the near future, then the most efficient, clean, and convenient methods of transportation and commerce may instead involve a combination of electric cars, conventional transit, and autonomous parking. Elon Musk’s unique mix of assets may be uniquely suited for this outcome.

Humans, Computers, and Telecommuters

Let’s discuss two sets of three: the land-labour-capital trinity of conventional economics, and the human-computer-telecommuter set that may soon become the three main categories of labour.

To state the obvious, the key relationship during the past generation has been the “capital” of North Atlantic economies (whether that capital be military power, technological innovation, or consumer demand), chiefly that of the United States, and the labour and “land” (most notably, the fossil fuels in that land) of Asia, chiefly that of the Chinese.

Even in recent years, this relationship between North Atlantic capital and Asian land and labour has arguably continued to intensify. Specifically, if we characterize “land” as being the type of energy production that has the greatest impact on local environments — if, for example, we define it as coal production, coal consumption, and the building of massive hydroelectric dams — then we can see that in recent years the employment of Asian “land” has continued to grow at a rapid pace relative to that of the North Atlantic economies.

This has been the result of a number of different significant trends: the growing “green economy” of Europe, the coal-to-gas electricity switchover in the United States that has been the result of shale gas production, the growth of coal and gas consumption in Japan as a result of Fukushima, the growth of hydroelectric power in China (though China’s coal industry growth has been flattening), and the growth of coal industries in southern Asia.

We know that poorer Asian populations in countries like China and India hold the weaker positions in this trade relationship. They supply the labour and “land” chiefly because the wealthier economies of the world mostly do not want to allow large-scale immigration or domestic environmental despoliation, yet are not able or charitable enough to furnish poor countries with capital wealth without demanding labour and natural resource wealth in return.

We also know that this global trade relationship might soon decrease to some extent, whether because of automation or protectionism in capital-rich countries, aging labour forces in Northeast Asia, or an attempt to reduce pollution in China.

The view of world trade decreasing because of automation and protectionism has become especially popular during the past year, because of political developments in both the US and China. Upon closer investigation, however, a reduction in trade may not actually be likely. The hitch here is the limitation of automation in wealthy economies. While computers and computer-run machines may now be excellent at doing tasks that humans are bad at — like being a grandmaster at chess or driving a truck for days without taking a pit stop — they are still terrible at a task that even human children find easy: manipulating objects.

The result of the limitation of automation may be the second set of three mentioned above: a human-computer-telecommuter division and cooperation of labour. Imagine, for example, an industrial or commercial site in the US that employs not only human labour, and not only machine labour, but instead a combination of a small number of on-site labourers, a large number of autonomous machines, and a large number of machines controlled by lower-wage labourers working remotely from poor locations in foreign countries.

In one sense, every party involved would gain in this relationship: rich countries would gain access to cheap labour without needing to outsource, poor countries would receive wages, and both would be allowed to harness the productive power of machines without having to wait until robotic technology is good enough to allow machines to replace labour altogether. Or without having to deal with the economic and social consequences of that day finally coming.

On the other hand, “telecommuters” might further income inequality within wealthy countries, by forcing labourers in those countries into even closer competition with labourers in poor countries. Moreover, it might make it more difficult to ignore the unfairness that exists as a result of real wages in rich countries far exceeding those of poor ones.

The effect of telecommuting — which includes, but is not limited to, a worker being able to control a machine that is located thousands of kilometres away — may be to make labour much more easily tradeable across long distances. Since “capital” is easily tradable too, this may leave “land” as the odd man out. Land considerations, for example the location of cheap and/or clean electricity, or of ports capable of importing natural resources from abroad, may therefore become more important, at least relative to labour considerations, when choosing where to locate a new industrial or commercial site.

A place like Iceland, for example, which has abundant and clean power, difficulty in exporting that power directly because of its island location, ports proximate to North America and Europe, and yet no real labour force to speak of, could use a combination of autonomous and remotely-controlled machines to become a major industrial or commercial production site. A similar thing may be true of economies like Quebec, Norway, Manitoba, or British Columbia.

Remote-controlled machines do not get very much press — even if you Google it, you will probably not find much, with the exception of medical tele-surgeries — when compared to discussions of a far future in which widespread, wholly autonomous machines run the labour force. What is so scary, or exciting, about the possibility of remote-controlled machines, and of telecommuting labour forces in general, is that we may not have to wait until the far future for them to become widespread.

The Lay of the Land

Imagine a map of the world in which land and sea are both drawn in the same colour, so as to be indistinguishable from one another. Imagine also that on this map areas that are inhabited by humans are drawn in a different colour than areas that are relatively uninhabited by humans. Finally, imagine that all of the oceans on this map are greatly shrunk in size, in order to account for the ease of transporting goods by sea, whereas all of the mountainous areas and hilly rainforests on the map are greatly increased in size, in order to account for the difficulty of transportation in such areas.

Such a map might reveal a great desert in the Northern Hemisphere, encompassing most of Asia, the Pacific Ocean, and the western half of North America. Within this great desert there would be a great oasis: Northeast Asia. There would also be many lesser oases, notably California. The Indian Subcontinent would also appear to be a great oasis, between the large deserts of Central Asia and the Indian Ocean, and the smaller deserts in and around Iran and Burma. Still, India would not be as remote an oasis as Northeast Asia.

This map would also reveal the key position of the habited parts of Europe and the Middle East, which would be seen as being extremely close to most of the inhabited parts of the Americas and Africa, as well as to much of the inhabited parts of Asia.

It would not now be surprising to learn that the watershed of the narrow Atlantic and Mediterranean seas is where an estimated two-thirds of global economic activity occurs. Nor would the fact that the Mediterranean economies have mostly struggled to keep up with those of the North Atlantic be surprising, given the mountains or deserts which surround the Mediterranean on all sides.

China, in contrast, would still seem to be in an isolated position. The mountains or hilly rainforests that make up much of the terrain of Southeast Asia and the east coast of India, plus the Tibetan plateau and Himalayas, would now appear to further isolate China from India. China would now also appear to be more internally divided. China’s non-natively-Mandarin-speaking areas along its southeast coast would now seem to be further from the Mandarin areas of the north (since mountainous lands lie between the two).

At the same time, China’s coastal areas would appear to be located closer to the rest of the world (including to the world’s Chinese diaspora, which disproportionately comes from southeast China), since the world’s seas would now appear to be much smaller than before. Japan, in contrast, would appear more internally unified when looked at using this map, as all of its lands border the sea and so would now seem to be closer to one another.

Going forward

Of course, this is a very, very rough imagining of the practical realities faced by human economics, based on a number of assumptions that may be wrong, including most importantly on the idea that navigability and habitability are among the most decisive economic and historical factors. Arguably, it helps to explain some key questions – why Europe and Middle Eastern religions spread so widely, why Atlantic and Mediterranean are economies are so large, why China has often struggled with internal regionalism, etc.. Even, however, if we do accept it as a decent model of the world today, it does not tell us how the world might soon change.

If modern technology tweaks the realities of this world-map we have tried to imagine — if, for instance, autonomous vehicles make it far easier to transport bulk cargo in mountainous areas, or in hilly rainforests — that could alter what we might expect the world economy, political or financial, to look like.

“Chindia” (and Chargentina)The term Chindia became somewhat popular during the BRIC boom a decade ago. It was used to refer to the idea that East Asia and South Asia would become economically much larger and somewhat better integrated with one another, together forming an Indo-Pacific economy that would rival (even if only a friendly rivalry) that of the Atlantic world, while also allowing China and India to dilute the global power of the US.
This scenario would also put Southeast Asia, Southwest China, and Northeast India in a key position in the world, controlling the trade routes (and much of the freshwater) of East and South Asia. Overland trade between China, Southeast Asia, and India might also threaten somewhat the position enjoyed by Singapore, Malaysia, and to a lesser extent Indonesia, all three of which benefit from ships sailing a long detour through the Straits of Malacca to get from the Pacific to the Indian Ocean. But, will any of this actually happen? It has not happened yet: trade between China and India remains quite low, given their sizes. We should also not overlook the possibility of a similar economic integration between two large countries that are separated by the world’s other great mountain range, the Andes, namely Chile and Argentina. Unlike China and India, these two nations speak the same language. Their population centres, though separated by high mountains, are located quite close to one another. Chile’s largest city, Santiago, and Argentina’s fourth largest city, Mendoza, are only 175 km apart, as the crow flies. But they are separated from one another by mountains reaching over 5 km high.Greater integration between Argentina and Chile could help both to balance against their much larger, Portuguese-speaking neighbour Brazil. It could perhaps then allow (Ch)Argentina and Brazil work together towards a greater level of South American or Latin American economic or political integration. This could turn out to be as important as anything that might happen between East Asia and South Asia.2. Return of the Mediterranean(s)

In our map of the world we saw the key position held by the Mediterranean, but also that the mountains of Mediterranean countries have limited their development as compared to the flatter lands like northern Europe and the eastern half of the United States. If, however, technology allows for economical transport in mountain areas, then the Mediterranean region might regain some of the influence it enjoyed historically.

Drainage Basin (millions of square km)

So too might other “mediterranean” seas that are surrounded in large part by rugged or rainforest lands. Most notable of these, perhaps, is the American mediterranean, the Gulf of Mexico & Caribbean, which, like the real Mediterranean, is centrally located (next to the narrow Atlantic, and between continents) but has much of its nearby population living in mountainous areas, in Mexico and Central America. The Caribbean, in turn, is near another “mediterranean” basin, the Amazon River and its many navigable tributaries.

3. The Heartland

Works of “Classic Geopolitics”, notably Halford Mackinder’s book Democratic Ideals and Reality (which I recommend reading), written a century ago at the end of WW1, lays out a vision of the world that is somewhat similar to the one I have tried to describe here. It identifies Europe and the Middle East as the economically-geographically central spot in the world, and argues that, given the Middle East’s relatively arid climate (the Middle East and North Africa had a far smaller population relative to Europe in 1919 than it does today), and given the spread of railways into landlocked areas, it would be the vast flat lands of Eastern Europe that might give rise to a political entity potentially capable of dominating Europe, the Middle East, and by extension the “World-Island” (meaning the Asia-Africa-Europe supercontinent), and by extension the world as a whole.

In this view, the devastating German-Russian wars of 1914-1917 and 1941-1945 were about who would control East Europe; the Cold War, the 1917-1918 part of WW1 (when Russia left the war and the US entered it), the 1939-1941 part of WW2 (before the Hitler-Stalin pact was broken), the Russo-Japanese war of 1904-1905, or various conflicts during the 19th century, such as the Crimean War or the Anglo-Russian “Great Game” in Central Asia and the Middle East, were about peripheral powers (Britain, France, Japan, the US, etc.) preventing an East European power like Russia and/or Prussia from expanding its influence.

Regardless of whether or not this Mackinderian perspective is an adequate one, it does seem that the central position of Europe, Eurasia and the Middle East arguably really does exist, and may persist. Eastern Europe continues to house by far the largest state and population in this area (Russia), and the Germans still by far the largest economy. But the more mountainous states and populations in Iran, Turkey, Ethiopia, and much of the Mediterranean and/or Arab worlds are also large, oil-rich, and centrally located. How this story will unfold going forward is anyone’s guess.

Unconventional NHL Strategies, continued

Playing 5.5-on-4
Pulling your goalie tends to be less beneficial on a power play, since icing calls can’t be called against penalty killers (so they can attempt a long shot at an empty net goal without a consequence if they miss) and since the marginal benefit of the extra attacker is smaller when you compare the difference between 6-on-5 and 6-on-4 to the difference between 5-on-5 and 6-on-5. As such, while trailing teams will still usually pull their goalie during the last minute or two of the game if they are on a power play, they tend not do so on a power play with, say, three minutes left in the game.

But what if, instead of pulling the goalie to get an extra attacker, a team instead uses its sixth man as a safety: positioning the sixth man around centre ice, so that he can help prevent a long empty net goal, while also being able to jump forward into the play as needed, in order (for example) to help prevent the puck from clearing the offensive zone, or to take a point shot. The sixth man would be playing, in effect, as both a goalie and a defenseman. And when he does jump into the zone at one point, a teammate from the opposite point could fall back to fill his safety position.

This strategy could perhaps even be usable at some times when not on a power play, in order to take advantage of having the puck in the offensive zone (or in order to take advantage of tired defenders) at a time earlier than the coach would otherwise be willing to pull the goalie. If, for example, a coach is not comfortable with pulling his goalie with 2.2 and 20 seconds left in the game, but would rather wait until the 2 minute mark to pull his goalie, he could have the option of using a 5.5-on-5 strategy for 20 seconds first.

2. Power play specialization and trade

Power plays arguably consist of two different skill-sets. One is getting the puck set up inside the offensive zone, the other is scoring a goal. Many of the league’s star players or power play specialists are excellent at both of these skill sets. But there is unlikely to be a clean overlap between the two. Getting the puck inside the zone on a power play, for example, depends more on skating, while scoring on a power play depends more on skills like passing, shooting, obstructing the goalie’s vision, and winning face-offs.

As a result, teams that do not have many great stars or power play specialists might want to think about a different strategy than the conventional “top power play unit, second power play unit” division of duties that NHL teams generally use. Instead, they may want to use a “specialization and trade” strategy: have one lineup optimized to getting the puck set up inside the zone, and then another lineup (some star players can play on both lineups) optimized for scoring a goal once already in the zone. The latter line would be subbed on the ice whenever there is a face-off inside the offensive zone on a power play. The former line could be subbed on (sometimes) on the fly when the opposing team shoots the puck down the length of the ice. This type of one-two punch strategy might also be useful at times playing 5-on-5.

Ontario: Low-Cost, High-Comfort Rail is much better than High-Speed, High-Cost Rail

Average is over. Long live average.

“High-speed rail” is a bit of misleading name: airplanes travel at a much faster speed. It might be better to call it “high-speed for rail” instead. Or call it “average-speed by rail”.

Of course, if you did refer to high-speed rail by any of those names, you probably wouldn’t have governments like Ontario’s pledging to spend 11 billion dollars to build a high-speed rail line from Toronto to Kitchener-Waterloo and London, Ontario. Even to those who support rail transport over less efficient, more polluting air and road transport, this move is difficult to justify from an economic perspective, given the population density of Southwest Ontario.

While high-speed rail is a good idea in populous areas where conventional rail options are already numerous (although even the Boston-New York-Washington corridor does not have one yet, which should set off alarm bells for those who think the Toronto-Guelph-Kitchener-London corridor, or even the larger Toronto-Windsor corridor, should build one) there are five main problems with high-speed rail in a place like Ontario.

One, it is much more expensive to build than conventional rail. Two, it has fewer stops and so can serve fewer cities than conventional rail. Three, it is less fuel-efficient than conventional rail. Four, it has much less capacity than conventional rail (if you double the speed of a rail line, you generally also must double the safe and comfortable distance required between each train, and so end up halving the capacity of the rail line) and so is much more expensive than conventional rail (unless wastefully subsidised by governments).

And fifth, yes it goes faster, but what’s the rush? What’s so bad about the existing 2.5 hour train from Toronto to London, Ontario…especially now that most people will soon have noise-cancelling wireless headphones and ultra-lightweight computers? And especially if e-commuting means that people will not have to make the trip as often as they otherwise might, or might be able to get work done while on the train. And anyway, don’t we continue to be told that automation and digital outsourcing going to do more and more of our work? Why exactly is someone rushing to or from Toronto so frequently that so much of our tax dollars should go to this “high-speed” train?

Instead of high-speed, high-cost rail, what Ontario could spend that 11 billion on instead is low-cost, high-comfort rail: rail on which it would be easy to work, relax, or sleep, and on which the needs of aging Baby Boomers who make up the biggest chunk of Ontario’s population, who are now already in their 60s and 70s, could be catered to more (making it easier to stow heavy suitcases, more bathroom capacity, etc.).

Indeed, what is really needed is not a way for to reach cities like London, Ontario or Kitchener-Waterloo, or even Windsor(-Detroit) without having to take a slow conventional train, but rather a way to reach more distant cities like Ottawa, Montreal, Chicago, and New York (all roughly 400-800 km from Toronto) without having to take a slow conventional train or an airplane. Ideally, we would have a train that is affordably priced, and so comfortable and smooth (i.e. with so few accelerations, decelerations, or bumps) that, at a low speed of 50-100 km an hour, a passenger could sleep easily though the night and wake up 400-800 km away. Even that would probably cost less than high-speed rail.

Boomeroomba, part 2

In a previous article, on the topic of playing tennis, I talked about the Boomer-Roomba test. An idea passes the Boomer-Roomba test if it is something that might be impacted by Baby Boomers reaching their 60s and 70s and by the introduction of everyday robots.

Downhill skiing, sadly, does not pass the test: many Baby Boomers will stop skiing in the near future. But what about less dangerous snow activities: snow shoeing, cross country skiing, sledding, skating, etc. etc.? These many Baby Boomers will still be able to do for a long time, with friends or with their kids and grandkids. Indeed many Boomers may soon have much more time for activities such as these, as they cut back on or retire from their jobs.

The management of snow and ice is also a task that robots (or at least, remote controlled machines) could be uniquely suited to handle. Clearing snow off roads, for example, is challenging mainly because it is both time-sensitive (you generally want it done as soon as possible, even if that means working overnight) and time-intensive (it takes a long time to clear heavy snow). Clearing snow off rooftops is even more difficult. For rural snowbelt areas that get walloped far more than even the snowiest cities like Syracuse, being able to plow and de-ice roads robotically could be a godsend. Advanced safety features in cars and busses, and advanced cruise control in cars, could also help these areas.

Creating and maintaining skating rinks — whether by clearing snow off a frozen lake, or by creating an artificial rink — is also highly labour-intensive work that could benefit from automation. And people really enjoy long-distance outdoor skating rinks, and skating on lakes. Skating also puts much less strain on the body than, for example, jogging does.

But perhaps the main reason that snowbelt areas might do well in the Boomer-Roomba test is a relative one: they might do better than northern cities in general. As Baby Boomers age, and as robots do more and more work in the economy in general, more people (whether a retired Boomer or an e-commuting Millennial) might move south, as snowbirds during the winter or (as many have already done) as year-round Sunbelt residents.

The reverse is also true, however: more people might move north in the summer, as reverse-snowbirds. Snowbelts could be well-placed, therefore, to become year-round attractions: serving reverse-snowbirds in the summer, and winter sports lovers in the winter. In contrast, non-snowbelt northern areas might see a boom in summer, and yet still see a continuation of the current trend of growing much more slowly than Sunbelt areas in general.

On Pulling Your Goalie: Unconventional Factors to Consider

NHL teams generally look at three factors to determine when to pull their goalie: the score of the game, the amount of time left remaining the game, and the location of the puck (i.e. if it is in the defensive zone, the goalie will not usually be pulled). It seems to me that two extra factors are needed:

the exhaustion level of the opposing team’s five on-ice players
the purpose of pulling your goalie

1. Exhaustion Level of Opposing Team’s Five On-Ice Players

Here’s a riddle: if your team was trailing by one goal, would you rather have the goalie pulled with 2 minutes left against a relatively well-rested defense or, instead, pulled with 3 minutes against a defense that is utterly exhausted as it is being caught on the ice during a really long shift?

There is no empirical evidence by which we can attempt to answer this riddle, because coaches almost never pull their goalies when down one goal with 3 minutes left. My guess, however, is that playing 6-on-5 against exhausted defenders with 3 minutes left may be better than playing 5-on-5 against exhausted defenders with 3 minutes left and then waiting until around the 2 minute mark to pull your goalie. Here’s why:

1) an exhausted defense is less likely to clear the zone and/or score an empty net goal

2) if an exhausted defense tries to score a long empty net goal and misses, resulting in an icing, then they will pay a big price for it: the other team will be able to bring on fresh players, which will make the difference in tiredness between the two teams even greater.

3) an exhausted defense playing 5-on-6 is less likely to get a lucky bounce or turnover that would allow them to clear the zone (or, if they do clear the zone, to clear it enough to get many of its players to reach the bench)

4) an exhausted defense playing 5-on-6 is more likely to have its goalie screened, so the odds of the goalie making a save to stop play and allow a line change is reduced.

5) by bringing a 6th attacker on the ice, you have the opportunity to seamlessly bring on a top player on who is fully rested himself.

6) pulling your goalie early means that the exhausted defense has less of a chance of winning the game by simply running down the clock. From a psychological perspective also, it may be more difficult for an exhausted player to muster his remaining energy when he knows he is not closed to being ‘saved by the bell’.

7) the exhausted players may not be that team’s best defenders; whereas with 1 or 2 minutes left in the game to play, a team normally has their best defenders on the ice. Moreover, if they cause an icing, you can bring on your own team’s best players

8) If the opposing team knows you might employ this strategy at some point during the game, they will be less willing to use their ‘coach’s challenge’ and so risk losing their time out. They will also be less willing to use their time out earlier in the game, even at times when they may need it. Your team gains an advantage by them being less willing to use their time out or coach’s challenge.

9) If the other team does manage to clear the zone and change lines, you can then use your own time out in order to rest your top line so that it can stay out on the ice for the rest of the game.

10) If you are playing a division rival or wild-card rival, and would like to deny them the chance of getting a point from an OT loss, this strategy gives you a (small) chance of winning the game in regulation

For all these reasons (some much more than others, obviously), I suspect that if you are facing a scenario where the opposing team’s line is exhausted with 3 minutes left and you are down a goal, you may be better off pulling your goalie then rather than waiting to do so with 2 minutes left against a better(-rested) line. If I were an NHL coach, I would try to simulate this scenario in practice during the offseason in order to try to answer this riddle. The reason I would run such an experiment is this: if it is true with 3 minutes left, what about with 4 minutes left? What about with 10? What if you were down by more than one goal? In other words, how exhausted do the opposing team’s players need to be, and much time left does there need to be, and how many goals down in the game do you need to be, to make this strategy worthwhile? We don’t know, as teams never try it.

We do know, though, that teams get caught out on long shifts fairly frequently. And we know that players’ effectiveness tends to drop dramatically when being caught on a long, tiring shift. So, if the strategy really were to prove effective, whichever team discovers it and implements it first may actually gain a significant advantage. (If it proved really effective, there may even be a case for waiting until the playoffs to deploy the strategy for the first time, in order prevent other teams from adopting the strategy themselves after seeing you use it). If successful, the benefit of simulating these scenarios in practice in the offseason could far outstrip the cost (of time and energy) that will be required to properly simulate the scenarios as required.

2. The Purpose of Pulling Your Goalie

We assume that the purpose of pulling your goalie must be to score a goal playing 6-on-5. But what about pulling your goalie to increase your odds of scoring a goal 5-on-5? Consider the following scenario: your team is trailing by a goal with 3 minutes left in the game, and is in control of the puck in the offensive zone. Some or all of your players on the ice are physically exhausted, and your best offensive player is on the bench. You would like to swap out one of your tired players to bring your star on the ice, but you don’t want to change on the fly because you are worried the other team might take advantage of the brief swap to try to gain control of the puck and clear the zone. Well, maybe you should think about pulling your goalie for a few seconds to bring him in, and then, once he joins his teammates in the offensive zone, have another player exit the game as quickly as possible so that your goalie can reenter the game. (This plan also works better if the players on both teams are tired, as at best they are only likely to get a chance to score an empty net goal from behind centre-ice, so they would be risking an icing). If done smoothly, you might be able to improve your odds of tying the game by trying this move.

goalie

Gliders, Gondolas, and Gravity

Gravity keeps us land-bound, most of the time. But there are at least two transportation technologies that work with rather than against gravity: cable-cars, which use the weight of anything they are carrying downhill to help lift anything they are carrying uphill; and gliders/parachutes, which mainly travel downhill.

The use of cable-cars is limited by their low carrying capacity (relative to trains, trucks, ships, etc.). The use of gliders and parachutes are limited by danger and imprecision, and by the fact that they must still fight gravity in order to get aloft in the first place.

New technologies may overcome these limitations, at least to a certain extent. In the case of cable-cars, low capacity can become less of a problem as a result of automation, not just in the operation of the cable-car but also in the loading, unloading, and warehousing of goods using the cable car. A cable car system could then run 24-7 (cable-cars are very quiet, so they are not annoying to run at night), with trucks being autonomously unloaded at the entrance of the cable-car and then autonomously unloaded and re-loaded onto another autonomous truck at the exit of the cable-car. Similarly, automation could allow a passenger to disembark his or her autonomous-valet-parking car or bus to get on a cable-car, then have another autonomous-valet-parking car or bus waiting for him or her at the cable-car’s exit.

Autonomous capabilities could be even more useful for cargo-carrying gliders or parachutes, helping to overcome the limitations of danger and of imprecision. The US military has been making great strides in this area in recent years in Afghanistan, with systems like JPADS (joint precision airdrop system) and research into gliders.

Of course, these systems must still use aircraft get airborne in the first place, which is not sustainable from either an economic or environmental standpoint. This is where things get interesting. What if, instead of gliders or parachutes being released from aircraft, they were instead released from cable-cars? In a mountainous or archipelagic region, this could allow goods and people to be transported during times when roads or ships are temporarily out of service as a result of snowfall, flash flooding, avalanches, earthquakes, low tides, etc.

Cable-cars might similarly be able to work well with cargo drones in general. They could serve as a sort of ferry for drones. By landing on a cable-car, drones could reduce their energy expenditure, recharge their batteries, and, as a result, reduce their battery sizes.

Everyone for Tennis?

These days, one way to sniff out a potential idea is to see if it passes the Boomer-Roomba test: if it is something that will benefit from Baby Boomers becoming senior citizens, and from the growing use of robots, you might be on to something.

One such idea, I suspect, is tennis — and also, perhaps, tennis’s more octagenarian-friendly sibling sports like badminton, pickleball, and ping pong.

Of course, tennis is already beloved around the globe, and played by young and old alike. But, the number of people playing it on a regular basis has typically been limited by at least one of the following factors:

— people participated in other sports/fitness activities instead

— people were busy with jobs or chores or raising children

— people had no tennis court easily accessible (or at least, not one that was not in use most of the time)

This last factor is particularly true for people in poorer countries; that is to say, for most people in the world. Tennis is a finnicky sport, compared to other sports like basketball, football, running, or even baseball, cricket, or road hockey. You can, for example, play basketball on a sloped driveway in front of your house, or on the road in front of your house. You can play football (soccer) in your backyard, or in a park, or in a parking lot with a surface that has been made uneven by years of being driven on. Tennis, in contrast, requires a far more level surface, and a much larger surface. Even, for example, when compared to playing full-court basketball, a tennis court can require about five times more floor space per player (if you are playing singles tennis):

Tennis courts’ size also makes tennis difficult to play indoors (indoor tennis bubble buildings notwithstanding), when compared to sports like basketball or, even more, when compared to indoor fitness gyms. (Tennis courts are even difficult to provide shade for, in comparison to, for instance, playing 3-on-3 basketball). This puts sports like tennis at a disadvantage, particularly in areas where weather gets hot, cold, or rainy—again, areas in which most people in the world live.

Anyway, back to the Boomeroomba test:

Boomers — tennis (and badminton, pickleball, etc, etc.) is more seniors-friendly than most other sports. Many Boomers (including Chinese Boomers, who are a decade or two younger than those in the West) still participate in sports like downhill skiing, long-distance cycling, or pickup basketball, but may stop or at least cut down on these sports as they age in years ahead.

Robots — robots may impact tennis in a number of ways. First, as robots are often meant as time-saving devices, and potentially as job-stealing devices, they may leave much more time for people to do things like play tennis. Second, robots may free up large amounts of commercial land, whether outdoors in parking lots or ndoors in malls or warehouses, as a result of technologies like autonomous vertical warehousing, autonomous delivery to consumers of goods bought online, or autonomous vehicles in general reducing the need for huge parking lots and making it easier for people to travel longer distances. Third, roomba-like robots can be ball boys.

So, tennis passes the test. Of course, so too might other sports — swimming, for example, or golf, or cross-country skiing or snow-shoeing, might also become common as a result of aging Boomers and of robots freeing up time and land. Moreso than tennis, however, those may be limited by their expense in many places.