Psychology, money and science

Non potest quisquam beate degere, qui se tantum intuetur, qui omnia ad utilitates suas convertit; alteri vivas oportet, si vis tibi vivere.

A couple thousand years ago, Roman philosopher Lucius Seneca theorized these wise ideals about how one should think about their time alive.  His own ideas were borrowed from ancient Asian religious scriptures, coded down an additional thousands of years before that.  But in the sometimes chaotic human progress since, we have seen tidal waves of sentiment that have allowed society to gyrate from what would be core religious ideals.  In the run-up to the global financial crisis, we see a perfect example of how capitalistic misjudgment can get carried away, in a macro scale.  Now the beliefs that Seneca had put forth, in the “Epistolæ Ad Lucilium”, is something we are trying in some respects to return to.  And as can be seen by the still embattled inequality topic in the news, we have room for improvement.  His message translates to “no man can live happily who regards himself alone, who turns everything to his own advantage.”  And “if thou wishest to live for thyself”, then first one must live for another.   

It’s not often that we can capture this sort of national sentiment among people, using recent quantitative surveys, and assess how citizens and consumers think about their own success (in relation to those of others).  So it’s very revealing when such a survey comes around that touches on usable data points, for us to see if we can deduce any societal opinion from it.  One such survey, for consumer finance giant American Express, was conducted by a top quantitative firm The Futures Company.  I crossed paths with their accomplished Chairman, as he has enjoyed a couple of my other popular economics articles (here, and here).  I discussed with him the idea of writing a research article on the survey results of LifeTwist, which can be available from his company. 

The online survey covered a “random sample” of more than 2,000 Americans.  For our purposes, we’ll focus on the presentation shown on pages 5 and 6.  The key report takeaways focus on how low money (by itself) is seen as a self-identified measure of success, while by some measures it is considered a more important topic in how we evaluate others (#20 for self, and #4 for others).  There are a number of ranked survey responses outside of the “top 10” that were censored, in presumably both reporting categories.  For reading ease we will color the terms “self” in blue, and “others” in grey.  Also equally challenging for statistics analysis of the survey output are a few other things.  First is that the survey response answers could be very different between the two categories.  Second is the sum of the response rates for the top 10 are not anywhere near equal in both categories.  Third if the same survey respondent was always answering for both categories, then it would be easier in conjunction with the other challenges noted, to show the responses based on major factor responses of the self category.  For example, separating out responses for those who generally valued their time and health, versus those who valued their family relationships.

This article will probe more deeply into the relationship between core psychology and these survey details.  See the chart below for the mathematical pattern in the top 10 survey response rates (shown in dotted lines). 

For example, in the survey shown, the #1 response for ourselves was garnered by 85% of the respondents, while for others was garnered by 61% of respondents.  It’s not easy to assess the general themes of the responses, and how they fit into our psychological view of money and success.  Something we’ll see through this article, and its cited research, is that happiness is more linked to success than money is.  And in fact we view internal happiness levels in others the most highly (again at 61%).  But that’s not the whole story; since we see the combination of the love other people have for their family and their general life experiences (at 42% and 31% respectively) to be worth even more.  Note that these two latter measures were ranked #2 and #3 among the top 10.  But they are likely driven off of the same type of motivational factors, and that theme may not register since it was split among survey respondents into two different measures.  Put differently, a single survey factor of “family life and life experiences”, could have easily come in at even higher than the 61% we gave to otherwise top ranked, internal happiness measure.

The approach we used here was more advanced from a mathematical perspective, and allows one to better understand how to interpret tabular descriptive statistics for our purpose of understanding broad differences in sentiment.  Also note that it is often traditional to not have mutually exclusive and completely exhaustive categories, in a number of both international government and other prominent reports as well.

Modern psychology -in fact- shows us that success and emotional strength go hand in hand.  Though many confuse themselves into what emotional strength is: it is not something you prove and compete for each day!  Before the financial crisis, the competitive pursuit of personal profits came at a cost not only in term of thinking about others, but also in terms of reflecting on what really matters in our own lives.  As Seneca philosophized, what truly matters is our ability the help others.  And there is recent empirical evidence of this.

In the bestselling book “Picture your Prosperity” (the author of which "loved" this article's approach), we see there is strength in merely having the freedom to not stress about money.  Further, this freedom then provides fertile ground to not just solve problems but to more crisply think about (and hence more likely to attain) one’s own higher purpose.  For those financially oriented, this act of positive thinking has a great return on investment!

For one recent U.S. study, Harvard Business School professor Norton -who also enjoyed this article- provided random subjects with money.  It ranged from $5, to $20, and in any case there were also instructions for the subject to either: spend the money on themselves, or spend the money on others.  Hours later the random participants were questioned about their happiness, and there was a large positive difference felt by those who were instructed to give the money away (versus those who spent the money on themselves).  You see, there was a higher purpose to the money and people’s own measure of success was attuned with what they could do with it for others.  As the 18^th century Methodist movement founder was quoted in his biographical “The Works of the Reverend John Wesley, A.M.”:

Having, First, gained all you can, and, Secondly saved all you can, Then give all you can.

The freedom to encourage positive thinking has also been adapted decades ago by the Russian and Eastern European Olympic training programs.  Here they segregated the Olympic-bound athletes into groups and each group was assigned a varying amount of mental training to do in lieu to physical training.  The Olympics’ results showed that those who were able to devote a larger amount of their time to mental exercise and visual-positive preparation had outperformed those who solely relied on “Rocky focused”, physical regimen.

There are little other constructs otherwise in the most elemental psychology (from Freud, to Jung) that otherwise speak directly to money.  Instead they focus, as one can now imagine, on probabilistically-nominal themes such as happiness, family, and dreams.  And recent great psychotherapists such as Irvin Yalom whose research includes excruciating details of San Francisco patients who are on the other extreme of emotional balance.  Those who are self-slaves only obsessing over the affection someone hasn’t provided, to the point they completely lose vision of their higher calling.  But in order to make the connection between these fundamental themes of psychology and the other data we showed here about being free to explore one’s higher purpose, we introduce the work of a 20^th century American psychologist Maslow.

In order to now reaggregate The Futures Company’s survey, we will apply these psychological and ordinal, needs.  The organization of these human needs are hierarchically stacked such that those related to general living and safety were given the low-level but foremost, layer of importance.  On the other and more advanced extreme, where few survey respondents answered, are those needs related to enhancing our esteem and self (not to be confused from the self-identified versus evaluation of others survey categories).  Similar to inequality frameworks, the Maslow model and patterns have been debated and mathematically reshaped over time, and by political regimes of other non-domestic countries. 

With the aforementioned probability set-up, see the new tabular format below for our ordinal scale, and we’ll analyze over both the counts as well as the more important absolute level of survey responses.

	SELF count	SELF%	OTHERS count	OTHERS%
SELF	2	130	1	61
ESTEEM	0	0	3	47
LOVE	1	81	3	81
SAFETY	6	457	2	26
GENERAL	1	81	1	27
TOTAL	10	749	10	242

Since we don’t have (no one does) a parametric form for this model, we can use the most advanced semi-parametric statistics to better understand the distinction between the survey output.

There are a few moving parts to this illustration above.  But the most critical thing though is to not overly analyze the movement among specific topics, but rather focus on the general differences again between the two dotted % lines (not the similar-flowing solid counts lines shown here just for completeness).  We will get into the math certainly in a moment.  For now we can see that there is a strong, statistically significant association that we have on valuing our own money most for the ability that it provides for general pleasures.  Things related to expressions of love and safety.  But when we think about the success of others, on the other hand, we see there is a strong tendency that we more strongly value others’ ability to use money for what it can buy (and to a smaller degree the freedom wealth can afford to not stress and simply enjoy the pursuit itself).

Financial and psychological studies have shown that it is at about $75,000 in wealth, where one no longer concerns about money merely for money sake, but rather can plan for a higher purpose.  One can’t retire of course on $75,000 (unless you only plan to live a year after retiring), but one doesn’t need to worry about where the next meal is coming from either.  We see from the survey responses that there is a disconnect, and concertedly so, in terms of people still improperly thinking the grass is greener elsewhere and so (unfortunately) that they must still struggle in order to keep up.  We are generally much more similar to our neighbors than we might imagine.  And as self-help, guru Anthony Robbins has shown in his own client examples, while there is a genuine struggle among many: many with assets several times the $75,000 level and who should feel highly comfortable with how good they really have it are instead paralyzed with immediate-term worry! 

Now for the probabilistic differences in the cumulative distribution functions shown (cdfs), we can apply something similar to an Anderson-Darling statistics to show the significance of the gap.  Of course given the basic large, blimp shape of the cdf gap in the illustration above, a Kolmogorov-Smirnov test statistic will suffice, particularly given its large test significance range (D=½, significance is 10%-20%).  The test statistics also show the self category of responses is exceptionally modal at basic necessities for money and hence more right skewed along higher psychological needs versus even a lognormal distribution!  Here is the Anderson-Darling test statistic calculation for our data (other examples worked out in Ch. 9 of “Statistics Topics”):

j                    = respondent choice among top 10

y_j                  = ordinal, respondent psychological level

u                   = 5 hierarchical levels

S_sum             = sum of all data(j) [S(y_j)]²[lnS**(y_j)-lnS**(y_j+1)]

F_sum             = sum of all data(j) [F(y_j)]²[lnF**(y_j+1)-lnF**(y_j)]

A²                 = -n*F**(u) + n*S_sum + n*F_sum

Where ** makes more sense to refer to our distribution interpretation of others’, and not the empirical self sample distribution.

In addition to showing the detailed non-parametric statistics test above, on a general level we showed the value in statistics to describe survey results in different and more important ways.  The original presentation by The Futures Company well works for some purposes, but we showed here how we can use the information as secondary research for other momentous insights.  Now if you have succeeded to this point in the article, congratulations on having made it.  The final quote should be something you both enjoy and internalize.   

To travel hopefully is a better thing than to arrive, and the true success is to labour.

Robert Stevenson penned this in the late 19^th century in “Viginibus Puerisque”.  In other words, with this one shot at life that we are given: enjoy the journey.  One must, as I am sure many of you do, stop every so often and smell the beautiful flowers laid along our path!

 

In an aside: there have been many nice acknowledgements that have come in, quicker than our articles have gone out.  One example is a citation in a recent weekend New York Times.  This citations page tries to preserve a sample list from many savvy professionals, across occupations.