Data from the CIA Factbook

Data from the CIA Factbook

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I write about this every now and then, because human fertility is falling faster then most demographers expect. Using the CIA Factbook for data, the present total fertility rate for the world is 2.407 births per woman that survives childbearing. That is down from 2.425 in 2014, 2.467 in 2012, and 2.489 in 2010.  At this rate, the world will be at replacement rate (2.1), somewhere between 2035 and 2040. That’s a lot earlier than most expect, and it makes me suggest that global population will top out somewhat below 9 Billion in 2050, lower and earlier than most expect.

Have a look at the Total Fertility Rate by group in the graph above. The largest nations for each cell are listed below the graph. Note Asian nations to the left, and African nations to the right.

Africa is so small, that the high birth rates have little global impact. Also, AIDS consumes their population, as do wars, malnutrition, etc.

The Arab world is also slowing in population growth. When Saudi Arabia at replacement rate (2.11), you can tell that the women are gaining the upper hand there, which is notable given the polygamy is permitted.

In the Developed world, who leads in fertility? Israel at 2.66. Next is France at 2.07 (Arabs), New Zealand at 2.03, Iceland at 2.01, Ireland at 1.98 (up considerably), UK at 1.89, Sweden at 1.88, and the US at 1.87, which is below replacement. The US still grows from immigration, as does France.

Most of the above is a quick update of my prior pieces, which have some additional crunchy insights.  When I look at the new data, I wonder if developed nations might not finally be waking up to the birth dearth.  Take a look at this graph:

Now, the bottom left is a little crammed.  What if I expand it?

I did the second graph in order to make the point that nations with fertility below 1.76 in 2010 tended to increase their fertility, while those above 1.76 tended to decrease it.  Not that you should trust any statistical analysis, but if you could, this is statistically significant at a level well above 99%.  (Note: this is an ordinary least squares regression.  Every “nation” is weighted equally.  If I get asked nicely, I could do a weighted least squares regression which gives heavy weight to China, India and the US, and less weight to Somalia, the West Bank, and Tonga.  I don’t think the result would change much.)

I’m chuckling a little bit as I write this, because this is an interesting result, and one that I never thought I would be writing when I started this project.  Interesting, huh?  My guess is that there is a limit to how much you can get people to reduce family sizes before they begin to question the idea.  Older parents may say, “What was that all about?” but children are usually fun and cute when they are little if they are reasonably disciplined.

One final note: I’ve been running into a lot of demographic articles of late, but this was the one that got me to write this: The World’s Most Populous Country Is Turning Gray.  The barbaric “One Child Policy” of China is having its impact; demography is often destiny.  That said, over the last six years China’s total fertility rate has moved from 1.54 to 1.60.

As it says in the article:

Births in 2016 reached 17.86 million, the most since 2000, rising by 1.91 million from 2015, the National Health and Family Planning Commission said this month. That still falls short of the official projection. Last June, the ministry estimated there would be an increase of 4 million new births every year until 2020. China will continue to implement the two-child policy to promote a balanced population, the plan said.

Fertility doesn’t turn on a dime.  When women conclude that the rewards of society (money, power, approval of peers) go to those with fewer children, that’s a tough cultural idea to overcome.  I would conclude that it will take a lot longer than a single five-year plan to turn around birthrates in China… if they can be turned around at all.  All across Asia, marriages happen at lesser rates, happen later, and produce fewer children.  China is one of the more notable examples.

PS — Picky note: the two-child policy in China is only available to a husband and wife where at least one is an “only child.”  It won’t create a balanced population near replacement rate, as everyone else must have only one child (with exceptions).

Photo Credit: eflon || The title of the article comes from a comment Greenberg supposedly made to Buffett when AIG was much bigger than Berkshire Hathaway — times change…

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The title of the article comes from a comment Greenberg supposedly made to Buffett when AIG was much bigger than Berkshire Hathaway [BRK] — times change…

It’s come to this: AIG has sought out reinsurance from BRK to cap the amount of losses they will pay for prior business written.  It’s quite a statement when you are willing to pay $10 billion in order to have BRK pay 80% of claims over $25 billion, up to $20 billion in total.  At $50 Billion in claims AIG is on its own again.

So what business was covered?  A lot.  This is the one of the biggest deals of its type, ever:

The agreement covers 80% of substantially all of AIG’s U.S. Commercial long-tail exposures for accident years 2015 and prior, which includes the largest part of AIG’s U.S. casualty exposures during that period. AIG will retain sole authority to handle and resolve claims, and NICO has various access, association and consultation rights.

Or as was said in the Wall Street Journal article:

The pact covers such product lines as workers’ compensation, directors’ and officers’ liability, professional indemnity, medical malpractice, commercial automobile and some other liability policies.

Now, AIG is not among the better P&C insurance companies for reserving out there.  2.5 years ago, they made the Aleph Blog Hall of Shame for P&C reserving.  Now if you would have looked on the last 10-K on page 296 for item 8, note 12, you would note that AIG’s reserving remained weak for 2014 and 2015 as losses and loss adjustment expenses incurred for the business of prior years continued positive.

For AIG, this puts a lot of its troubles behind it, after the upcoming writeoff (from the WSJ article):

AIG, one of the biggest sellers of insurance by volume to businesses around the globe, also said it expects a material fourth-quarter charge to boost its claims reserves. AIG declined to comment on the possible size. Its fourth-quarter earnings will be released next month.

For BRK, this is an opportunity to make money investing the $10 billion as claims on the long-tail business get paid out slowly.  It’s called float, which isn’t magic, but Buffett has done better than most at investing the float, and choosing insurance business to write and reinsure that doesn’t result in large losses for BRK.

I expect BRK to make an underwriting profit on this, but let’s assume the worst, that BRK pays out the full $20 billion.  Say the claims come at a rate of $5 billion/year.  The average payout period would be 7.5 years, and BRK would have to earn 9.2% on the float to break even.  At $3.75B/yr, the figures would be 10 years and 6.9%.  At $2.5B/yr, 15 years and 4.6%.

This doesn’t seem so bad to me — now I don’t know how bad reserve development will be for AIG, but BRK is usually pretty careful about underwriting this sort of thing. That said BRK has a lot of excess cash sitting around already, and desirable targets for large investments are few.  This had better make an underwriting profit, or a small loss, or maybe Buffett is ready for the market to fall apart, and thus the rate he can earn goes up.

All that said, it is an interesting chapter in the relationship between the two companies.  If BRK wasn’t the dominant insurance company of the US after the 2008 financial crisis, it definitely is now.

Full disclosure: long BRK/B for myself and clients

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I was driving to a meeting of the Baltimore CFA Society, and listening to Bloomberg Radio, which was carrying President-Elect Trump’s Press Conference. I didn’t think too much about what I heard until Sheri Dillon talk about what was being done to eliminate conflicts of interest. Here is an excerpt:

Some have asked questions. Why not divest? Why not just sell everything? Form of blind trust. And I’d like to turn to addressing some of those questions now.

Selling, first and foremost, would not eliminate possibilities of conflicts of interest. In fact, it would exacerbate them. The Trump brand is key to the value of the Trump Organization’s assets. If President-elect Trump sold his brand, he would be entitled to royalties for the use of it, and this would result in the trust retaining an interest in the brand without the ability to assure that it does not exploit the office of the presidency.

[snip]

Some people have suggested that the Trump — that President-elect Trump could bundle the assets and turn the Trump Organization into a public company. Anyone who has ever gone through this extraordinarily cumbersome and complicated process knows that it is a non-starter. It is not realistic and it would be inappropriate for the Trump Organization.

It went on from there, but I choked on the last paragraph that I quoted above. (Credit: New York Times, not all accounts carried the remarks of Ms. Dillon, a prominent attorney with the firm Morgan Lewis who structured the agreements for Trump)  As I said before:

An IPO of the Trump Organization was realistic.  I’m not saying it could have been done by the inauguration, but certainly by the end of 2017, and likely a lot earlier.  I’ve seen insurance companies go through IPO processes that took a matter of months, a few because they had to sell the company to raise liquidity quickly for some reason.

In an IPO, Trump, all of Trump’s children and anyone else with an equity interest would have gotten their proportionate share of the new public company.  Trump could have provided a lot of shares for the IPO, and instructed the trustee for his assets to sell it off the remainder over the next year or so.

While difficult, this would not have been impossible or imprudent.  Trump might lose some value in the process, but hey, that should be part of the cost for a very wealthy man who becomes President of the US.  There would be the countervailing advantage that all capital gains are eliminated, and who knows, that might settle his existing negotiations with the IRS.

Ending the counterfactual, though conflict of interest rules don’t apply to the President, Trump had an opportunity to eliminate all conflicts of interest, and did not take it.

PS — Many major hotels are in the “name licensing” business — I also don’t buy the argument that Trump could not sell off the organization in entire, with no future payments for the rights of using the name.  A bright businessman could create a new brand easily.  It’s been done before.

Photo Credit: D.C.Atty || Scrawled in 2008, AFTER the crash started

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Comments are always appreciated from readers, if they are polite.  Here’s a recent one from the piece Distrust Forecasts.

You made one statement that I don’t really understand. “Most forecasters only think about income statements. Most of the limits stem from balance sheets proving insufficient, or cash flows inverting, and staying that way for a while.”

What is the danger of balance sheets proving insufficient? Does that mean that the company doesn’t have enough cash to cover their ‘burn rate’?

Not having enough cash to cover the burn rate can be an example of this.  Let me back up a bit, and speak generally before focusing.

Whether economists, quantitative analysts, chartists or guys who pull numbers out of the air, most people do not consider balance sheets when making predictions.  (Counterexample: analysts at the ratings agencies.)  It is much easier to assume a world where there are no limits to borrowing.  Practical example #1 would be home owners and buyers during the last financial crisis, together with the banks, shadow banks, and government sponsored enterprises that financed them.

In economies that have significant private debts, growth is limited, because of higher default probabilities/severity, and less capability of borrowing more should defaults tarry.  Most firms don’t like issuing equity, except as a last resort, so restricted ability to borrow limits growth. High debt among consumers limits growth in another way — they have less borrowing capacity and many feel less comfortable borrowing anyway.

Figuring out when there is “too much debt” is a squishy concept at any level — household, company, government, economy, etc.  It’s not as if you get to a magic number and things go haywire.  People have a hard time dealing with the idea that as leverage rises, so does the probability of default and the severity of default should it happen.  You can get to really high amounts of leverage and things still hold together for a while — there may be extenuating circumstances allowing it to work longer — just as in other cases, a failure in one area triggers a lot more failures as lenders stop lending, and those with inadequate liquidity can refinance and then fail.

Three More Reasons to Distrust Predictions

1) Media Effects — the media does not get the best people on the tube — they get those that are the most entertaining.  This encourages extreme predictions.  The same applies to people who make predictions in books — those that make extreme predictions sell more books.  As an example, consider this post from Ben Carlson on Harry Dent.  Harry Dent hasn’t been right in a long time, but it doesn’t stop him from making more extreme predictions.

For more on why you should ignore the media, you can read this ancient article that I wrote for RealMoney in 2005, and updated in 2013.

2) Momentum Effects — this one is two-sided.  There are momentum effects in the market, so it’s not bogus to shade near term estimates based off of what has happened recently.  There are two problems though — the longer and more severe the rise or fall, the more you should start downplaying momentum, and increasingly think mean-reversion.  Don’t argue for a high returning year when valuations are stretched, and vice-versa for large market falls when valuations are compressed.

The second thing is kind of a media effect when you begin seeing articles like “Everyone Ought to be Rich,” etc.  “Dow 36,000”-type predictions come near the end of bull markets, just as “The Death of Equities’ comes at the end of Bear Markets.  The media always shows up late; retail shows up late; the nuttiest books show up late.  Occasionally it will fell like books and pundits are playing “Can you top this?” near the end of a cycle.

3) Spurious Math — Whether it is the geometry of charts or the statistical optimization of regression, it is easy to argue for trends persisting longer than they should.  We should always try to think beyond the math to the human processes that the math is describing.  What levels of valuation or indebtedness are implied?  Setting new records in either is always possible, but it is not the most likely occurrence.

With that, be skeptical of forecasts.

 

Photo Credit: New America || Could only drive through the rear-view mirror

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This is the time of year where lots of stray forecasts get given.  I got tired enough of it, that I had to turn off my favorite radio station, Bloomberg Radio, after hearing too many of them.  I recommend that you ignore forecasts, and even the average of them.  I’ll give you some reasons why:

  • Most forecasters don’t have a good method for generating their forecasts.  Most of them represent the present plus their long-term bullishness or bearishness.  They might be right in the long-run.  The long-run is easier to forecast, in my opinion, because a lot of noise cancels out.
  • Most forecasters have no serious money on the line regarding what they are forecasting.  Aside from loss of reputation, there is no real loss to being wrong.  Even the reputational loss issue is a weak one, because Wall Street generally has no memory.  Why?  Enough things get predicted that pundits can point to something that they got right, at least in some years.  Memories are short on Wall Street, anyway.
  • The few big players that make public forecasts have already bought in to their theses, and only have limited power to continue buying their ideas, particularly if they are wrong.  This is particularly true in hedge funds, and leveraged financial firms.
  • Forecasts are bad at turning points, and average forecasts by nature abhor turning points.  That’s when you would need a forecast the most, when conditions are going to change.  If a forecast presumes “sunny weather” on an ordinary basis it’s not much of a forecast.
  • Most forecasters only think about income statements.  Most of the limits stem from balance sheets proving insufficient, or cash flows inverting, and staying that way for a while.
  • Most forecasts also presume good responses from policymakers, and even when they are right, they tend to be slow.
  • Forecasts almost always presume stability of external systems that the system that holds the forecasted variable is only a part of.  Not that anyone is going to forecast a war between major powers (at present), or a cataclysm greater than the influenza epidemic of 1918 (1-2% of people die), but are users of a forecast going to wholeheartedly believe it, such that if a significant disaster does strike, they are totally bereft?  When is the last time we had a trade war or a payments crisis?  Globalization and the greater division of labor is wonderful, but what happens if it goes backward, or a major nation like France faces a scenario like the PIIGS did?

I leave aside the “surprises”-type documents, which are an interesting parlor game, but have their own excuses built-in.

My advice for you is simple.  Be ready for both bad and good times.  You can’t tell what is going to happen.  Valuations are stretched but not nuts, which justifies a neutral risk posture.  Keep dry powder for adverse situations.

And, from David at the Aleph Blog, have a happy 2017.