This article was posted on Thursday, Feb 01, 2018

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It was a long weekend and Emily was home, again. She was sprawled on the couch nibbling on peanut-butter cups and sipping pink moscoto from a coffee mug, in a pensive mood. The television was on but she wasn’t watching.

Emily’s real estate investments had prospered and as she thought about the future her mind drifted to the economic forecasts she’d recently seen. They were mixed. Nobody really knew what was going to happen, but that did not stop them from speculating. Some esteemed business minds thought everything was fine and the economy would continue strengthening. These Panglossians pointed out that unemployment was the lowest since 2000. Property values were climbing due to low inventory. Interest rates had crept up, but were still historically low. Stocks were at record levels and the bulls argued that stocks remained underpriced.  An often expressed opinion was that the economy would perk along quite nicely, due largely to the new favorable tax laws, until late 2020. Left unclear was what would happen after that.

Other, more dystopian, commentators had a darker perspective. They noted that, going back to 1854, the only two economic expansions longer than the present one were from March 1991 to March 2001 (120 months) and February 1961 to December 1969 (106 months). The present expansion is now 103 months old, the third longest in the past 164 years. That’s getting kind of long in the tooth. If the economy continues growing until late 2020 the current expansion, which began in June 2009, would become the longest in history. But nothing, the commentators remind us, goes on forever, and the next recession could begin any day.

Whether one sides with the Panglossians or the dystopians, certainly there will one day be another recession. It is inevitable. So the question in Emily’s mind right now was, “If it happened, how could I come out the other side with all or most of my net worth intact?” 

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Length and Depth

It probably, she thought, depended a lot on the depth and the duration of the next recession. After all, you have to know what to prepare for. A recession is identified as two consecutive quarters of negative economic growth, but that doesn’t mean all recessions are the same. Some downturns are long and deep. Some are short and not terribly disruptive. And others are like a Chinese menu: choose one characteristic from Column A and one from Column B.

Emily did a little research and found that there have been 33 recognized recessions since 1854, with 21 of them prior to 1945 (an average of one recession every 52 months). The longest was the 1873 recession (65 months) and the shortest in 1918 (7 months).  Thirteen of these 21 recessions featured economic declines of 20% or more.

But things changed dramatically after WWII. There have been twelve recessions since 1945 (an average of one every 72 months), with the longest being the Great Recession of 2007 (18 months) and the shortest in 1980 (6 months). None of the economic declines got anywhere close to 20%. In fact, the deepest drawdown among these 12 post-WWII recessions was in 1981 (11%) and the shallowest in 1945 (5%).

Standard Deviation

That got her attention: since the end of WWII recessions have been fewer, shorter and milder than the pre-war recessions. That being the case, Emily thought that using the more recent post-WWII data would give a better idea of what the next recession might look like. There were no guarantees, of course, but that was where her mind was going.

She thought the two data points she needed to find were “how long” and “how deep”.

To do this she resolved to determine the standard deviation (SD) of both “deep” and “long”. That would tell her how deep most of the recessions were, and how long most of them lasted.

The standard deviation is a measure of central tendency. Imagine the classic bell shaped curve, with half the data points to the left of the average (also called the “mean”) and half to the right. In a normally distributed sample, 68% of the data points would be, by definition, within one standard deviation (plus or minus) of the mean. For example, if we took as our data set the whole numbers from 1 to 11, the mean (average) would be 6, and one standard deviation of the mean would range from 3 to 9. Sixty-eight percent of the numbers 1 to 11 would be in that range. Half would be less than 6, and half more than 6.

Another example: if we graphed the heights of all the children in the local fourth grade, 34% of them would be within one-half standard deviation shorter than the class average, and 34% would be within one-half standard deviation taller than the class average. Ergo, one (whole) standard deviation contains 68% of the samples. That’s why the standard deviation is important: it reveals where over 2/3rds of the data points lie. If you were a wagering person and placed all your bets within one SD of the average, over time 68% of your bets would be winners.

Running the numbers through an on-line calculator revealed that the average length of these twelve post WWII recessions was 11 months, with a standard deviation of 3.8 months. Emily concluded that two/thirds of the recent recessions lasted between 7 and 15 months (rounded). That told her how long most recessions lasted.

The thing is, economic dips are not recognized as formal recessions until the dip has persisted for at least six months. That means that she would probably have, once the decline was officially recognized as a recession, between 1 and 9 months to buy the assets she wanted “on the dip”.

Emily then ran the numbers for the severity of the recession and found that the average recession experienced an 8% (rounded) economic loss, and that in 68% of the post WWII recessions the economic losses ranged from 5.8% to 9.4%.

Briefly, then, she thought that the inevitable next recession would not be quite as devastating as the most dystopian forecasters expected. From this data it appears the most likely economic decline would last between seven and 15 months, and the hits to the GNP (Gross National Product) would probably range from 5.8% to 9.4%. For Emily, as with most people, this would be an entirely survivable event. 

Yes, But

Emily learned early, in Sister Mary Theresa’s third grade class, to always check her work because, as Sister Mary said, there’s always a YesBut. Emily refreshed her mug of moscoto and reviewed the reasons for some of the recent recessions. Maybe the cause affected the results. The 1973 Recession was caused by the quadrupling of oil prices, yet it only reduced overall enterprise in the USA by 3.2%. As central as oil is to a developed economy, raising its price 400% only reduced the underlying economy by a touch over 3%. She thought that was astonishing. 

Another Measure of Loss

However, the GNP is not the stock market. Measurements of the Gross National Product are snapshots of the economy taken every three months. “Bill, how’s the GNP doing?” “It’s down 3%% this quarter, Mike.” The stock market takes those snapshots and extends the change into the future. A 3% loss now can make a huge difference in a stock’s value when compounded over the next thirty years. Technically, it’s called the “discounted value of future returns”, and in that way it can be argued that the stock market provides a better indication of the future economy than the GNP numbers.

This can be seen by tracking the S&P 500, an index of the 500 largest public companies in the USA. The S&P 500 was at 117.5 in the year prior to the 1973 recession. At the bottom, the S&P was at 67, a loss of 43%.

Then there was the Dot-Com Recession in 2000, which reduced the total economy by 0.3%. It had a negligible effect on GNP, but the effect on the stock market was meaningful. In 2000 the S&P hit 1485, dropping during the recession to 837, a loss of 44%. The tech stock sector fell over 75%.

Ok, so the recession hit and – to review – the economy dropped 0.3%, the S&P dropped 44%, and the dot.coms dropped by 75%. We’re seeing kind of a ripple effect here, with the greatest effects on the imploding sector and lesser consequences as we move towards the economy as a whole. Throw a pebble into the pond and there’s a splash when the pebble hits the water. Ripples form, expand from the center, and dissipate as they do so.

Most recently there was the infamous Housing Bubble recession from 2007-2009, which shrunk the economy by 5.1%. In early 2007 the S&P hit 2009, and subsequently collapsed to 805, a 60% loss.

Focusing on the change in the S&P, Emily saw the issue immediately. The first two recessions were mostly contained within their sector (oil, technology). Effects of the Housing Recession were deeper because it was a credit problem and everything depends on credit. Credit is possibly the biggest driver of the economy. Tighter credit affects everybody. It wasn’t just in housing, or the profits Home Depot earns, or costs of buying or refinancing a property. It was also the secondary market where mortgages are bought and sold again and again for the next 30 years, as various banks, pension funds, and insurance companies seek to manage their obligations. All of this caused Emily to conclude that the more sectors impacted, the greater the effect. 

Oh, My!

There is no more vital sector to the American economy than credit. It impacts all economic sectors. At some level every financial transaction in America is backed in some manner by credit. The money for paychecks, dividends, bond interest, and rents comes from credit extended earlier in the chain of transactions.

What if credit just . . . froze up? What if the next recession was a credit crunch covering all or nearly all sectors of the economy? It would be much worse than the Housing Bubble.

This is not a difficult scenario to imagine. We’ve just passed through a period when interest rates were artificially maintained at, someone wrote, “the lowest in 5,000 years”. Rates are now climbing. It is not unreasonable to believe that every credit-worthy person and every credit-worthy company who was willing and able has already refinanced their loan(s) and even opened new credit facilities. There is good reason borrowers did that: money was cheap. There is equally good reason lenders cooperated: cheap money is (by definition) risk-free money. But now rates are climbing and risk is stirring. Payments easily made when the 10 year Treasury rates were 1.50% (July, 2016) are a little more difficult when they approach 2.50%. That may not sound like much, but it is a 67% increase. It is fully equivalent to the interest on 8% money going to a bit over 13%. The higher rates climb, the more business lines of credit are reduced (mostly over the borrower’s objections). Factoring costs more. New automobiles are offered at 72 months interest-free financing and there are fewer takers. Foreclosures are again 3-to-a-block. Lending money becomes riskier, and riskier money is more expensive. When interest rates climb, values drop. When values drop, the economy tends towards the deflationary. The potential is much worse than 2008 Housing Bubble because, due to a decade of historically low rates, every sector of the economy is now overborrowed. That makes every sector vulnerable. The dystopians may be proved optimistic.

Emily started this theme by wondering how a person could turn such a dark future into lemonade. She now saw that monetizing her assets, so she would have the cash available to make new investments at very friendly prices sometime in the future would be, probably, a reasonable step. She also knew she’d never do that because she lacked the most essential data point: when. Knowing that something will happen (the Sun will burn itself out) is not actionable until you know when it will happen (on Tuesday). Knowing  when makes all the difference. To be actionable, both the event and the time it will occur must be known. We know only that eventually another recession will happen and it may not be limited to only one or two sectors of the economy. It will probably be severe. We know we should be prepared for it, as much as we can. But that knowledge cannot be acted upon just yet because we don’t know when.

Emily knew that theoretically in these matters, it was better to be a year too early than a day too late, but she still felt no urgency. Maybe those optimistic forecasters were right, and the economy would continue to perk along quite nicely for a couple of years or perhaps even more. If it was really going to happen, somebody would know when. She decided her best option was to employ watchful waiting. Emily’s mood lightened as emptied the last of the moscoto.


This article is for informational purposes only and is not intended as professional advice. For specific circumstances, please contact an appropriately licensed professional.

Klarise Yahya is a Commercial Mortgage Broker, BRE: 00957107  MLO: 249261. If you are thinking of refinancing or purchasing real estate, Klarise Yahya can probably help. Find out how much loan the building will support. For a complimentary mortgage analysis, please call her at (818) 414-7830 or email [email protected]