To my surprise, it was Benjmain Franklin who coined the phrase ‘Time is Money’ (although like most of Western civilisation he was simply repackaging an idea inherited from the ancient Greeks).
Since time is the most precious commodity we have, it provides an uncomplicated measure of how important something is. Not unreasonably, we conclude the more time someone spends doing something, the more valuable (or enjoyable or vital) they consider it to be. As a printer-scientist-statesman-author-cum-diplomat, Franklin certainly filled time with things that were important to him.
Back in April, the National Endowment for the Arts (NEA) released one of their periodic research notes entitled ‘Time and Money: Using Federal Data to Measure the Value of the Arts’. While this is now a couple of months old, it seems like as good a place as any for Bad Culture to start. Here is the opening sentence from the abstract:
This Note examines large datasets from multiple federal sources including the U.S. Economic Census, the Bureau of Economic Analysis (BEA), and the Bureau of Labor Statistics (BLS), to arrive at monetary and non-monetary value measurements of the nation’s performing arts sector.
The Key Findings from this report are short and eminently readable, so I won’t repeat them verbatim here. Suffice to say that the report suggests Americans value the performing arts highly, due to some big numbers derived from the time and money spent on them.
Digging a bit deeper, the standard categories used in federal datasets are not designed to facilitate this kind of analysis in the arts. For example, the relevant category in the Bureau of Labor Statistics Consumer Expenditure Survey is ‘Admissions to movies, theatres and amusement parks’. I’m assuming that, in an ideal world, the NEA would disaggregate at least two of these subheadings from the numbers. (A similar issue arises if you try to quantify time spent in galleries. These are commonly subsumed into a general ‘Museums’ category, although it doesn’t doesn’t really come up here as the focus is on the performing arts).
On monetary statistics where direct comparisons can be made, the performing arts come out as less valuable than sports, and have mixed results when compared to movie-going. Drawing conclusions from such general and high level numbers is hard, but this kind of relative analysis is rarely done and is all the more interesting for it.
Section 3 presents summarised time use data, based on day long diaries in which people denote their activities. Here the performing arts look to be well attended and sociable. Again, the data is notable for presenting the kind of relative statistics that aren’t always available – performing arts attendance is done later in the evening than sports, while museum visits occur at lunchtime. More people go to the theatre than to a baseball game with their spouse.
The NEA has had a difficult few months (although it has a difficult few months every year at budget time) but irrespective of the merits of that debate, I’m a devotee of their research notes and reports. They generally contain interesting interpretations of reliable data, but don’t overstate the conclusions that can be drawn. This is not always the case in the cultural sector, hence the blog.
Where their methodology is imperfect, they are upfront about it. Where it is unclear whether data is showing correlation or causality, the NEA themselves point this out the question (their comprehensive 2010 report on technology and engagement is a case in point). Time and Money is no exception, as they note the difficulties in each dataset and the inherent limitations of trying to assign value on temporal and monetary statistics alone.
That said, I’d like to a level of analysis above and beyond what they pesent here. The relative statistics are interesting, but I wonder about the possibility of assessing the level of separation between populations that attend sports, arts, movies and other cultural activities. To put it another way, in a Venn diagram showing attendance for each category, how significant is the overlap between the arts circle and the other cultural circles? To put it still another way, are we talking about a small number of Ben Franklin-types who engage in all types of cultural activity, or separate groups who engage in one activity but don’t stray across to others. I’m not sure whether it is way the dataset is collected that prevents this, or whether it is simply outside their scope.
The ‘Final Thoughts’ section is also of particular interest as a whistle stop tour through the benefits and difficulties of performing a quantifiable assessment of the value of the cultural activity. It looks at similar techniques and comes to similar conclusions as to the recent DCMS report Measuring the Value of Culture, although it is less dense and more accessible. I would love to see how the performing arts compare to sports, museums, TV watching and surfing the internet across different measurement techniques.
The ‘Final Thoughts’ promises a follow up report on Value Added methods of assessing the value of the arts. That promises tomake good reading, and we will certainly cover it here.
Finally, I note with satisfaction that an average of 0.5 million Americans write every day for personal pleasure, and that they write (on average) for 1.5 hours, generally in the evening. Alas, it isn’t possible from the data to tell how many are constructing poetry or prose, and how many merely doing something more functional.