Archive for October, 2014
| Gabriel |
The transformations of the television industry are an endlessly fascinating subject that I spend a lot of time ruminating on but haven’t ever, you know, actually published on. We can start with a few basic technological shifts, specifically the DVR and broadband internet. Both technologies have the effect that people are watching fewer commercials. From this we can infer that advertisers will have a pronounced preference for “DVR-proof” advertising.* One form of this is product shots, which are indeed a big deal nowadays, especially in the reality competition genre. Of course product shots are inherently cumbersome and are pretty much the antithesis of the scatter advertising market insofar as they require commitments during pre-production which is even more extreme than up-fronts and which is why we long ago got past the age of Texaco Star Theatre. So basically, the 30 second spot you will always have with you. Or rather, the demand for the 30 second spot you will always have with you and the question is can we find a type of programming where people watch the ads. (Note that the recent Laureate Jean Tirole did work on this issue, as explained by Alex Tabarrok at MR).
In practice getting people to watch spot advertising means programming that has to be watched live and in practice that in turn means sports.** Thus it is entirely predictable that advertisers will pay a premium for sports. It is also predictable that the cable industry will pay a premium for sports because must-watch ephemera is a good insurance policy against cord-cutting. Moreover, as a straight-forward Ricardian rent type issue, we would predict that this increased demand would accrue to the owners of factor inputs: athletes, team owners, and (in the short-run) the owners of cable channels with contracts to carry sports content. Indeed this has basically all happened. You’ve got ESPN being the cash cow of Disney, ESPN and TNT in turn signing a $24 billion deal with the NBA, an NBA team selling for $2 billion, and Kobe Bryant making $30 million in salary. Basically, there’s a ton of money in DVR-proof sports, both from advertising and from the ever-rising carriage fees that get passed on in the form of ever rising basic cable rates. (I imagine a Johnny Cash parody, “how high’s the carriage fees mama? 6 bucks per sub and rising.”).
Here’s something else that is entirely predictable from these premises: we should have declining viewership for sports. Think about it, you have widget A and widget B. Widget A has a user experience that’s the same as it’s always been (ie, you got to watch it when it’s on and sit through the ads) but the price is rapidly increasing (it used to be you could get it over broadcast or just from a basic cable package that was relatively cheap). In contrast you have widget B which has a dramatically improved user experience (you can watch every episode ever on-demand whenever you feel like it without ads and do so on your tv, tablet, or whatever) and a rapidly declining price (if you’re willing to wait for the previous season, scripted content is practically free). If you’re the marginal viewer who ex ante finds sports and scripted equally compelling, it seems like as sports get more expensive and you keep having to watch ads, whereas scripted gets dirt cheap, ad-free, and generally more convenient, the marginal viewer would give up sports, watch last season’s episodes of Breaking Bad on Netflix, be blissfully unaware of major advertising campaigns, and pocket the $50 difference between a basic cable package and a $10 Netflix subscription. Of course you wouldn’t predict that the kinds of guys who put body paint on their naked torsos would give up on sports just because Netflix has every season of Frasier, but you would predict that at the population level interest in sports would decline slightly to moderately.
The weird thing is that this latter prediction didn’t happen. During exactly the same period over which sports got more expensive in absolute terms and there was declining direct cost and hassle for close substitutes, viewership for sports increased. From 2003 to 2013, sports viewership was up 27%. Or rather, baseball isn’t doing so great and basketball is holding its own, but holy moly, people love football. If you look at both the top events and top series on tv, it’s basically football, football, some other crap, and more football. (Also note that football doesn’t appear in the “time-shifted” lists, meaning that people do watch the ads). And it’s not just that people have always liked football or that non-football content is weakening, but football is growing in absolute popularity.
That this would happen in an era of DVRs and streaming is nuts, and kind of goes contrary to the whole notion of substitutes. I mean, I just can’t understand how when one thing gets more expensive and something else that’s similar gets a lot cheaper and lower hassle, that you see people flocking to the thing that is more money in absolute terms and more hassle in relative terms.*** Maybe we just need to keep heightening the contradictions and then eventually the system will unravel, but this doesn’t explain why we’ve seen a medium-run fairly substantial rise in sports viewership instead of just stability with a bit of noise.
I’m sure one of my commenters is smarter than me and can explain why either my premises or logic is incorrect, but at least to me this looks like an anomaly. And even if we can ultimately find some auxiliary hypothesis that explains why of course we’d predict a rise in sports viewership if we only considered that [your brilliant ex post explanation goes here],**** let’s keep in mind that this is all ex post, and adjust down our confidence about making social scientific predictive inferences accordingly. A theory like decline in total cost of widget B will lead to substitution of widget B for widget A is a pretty good theory and if its predictions don’t hold in the face of something like bigger linebackers or more exciting editing for instant replay, then you have to wonder how much any theory can get us.
*If we’re a bit more creative we could also infer that the market information regime for audience ratings will see a lot of contentious changes.
**It is interesting that the tv networks aggressively promote Twitter in order to promote live viewing of scripted content and news, but at this point the idea that networks will hashtag their way to a higher “C3” ratings is pretty niche/speculative.
*** The closest parallel I can think of is that it’s the easy-going mainline Protestant churches that have seen especially steep declines in attendance/membership and the more personally demanding churches that are relatively strong. I may have to rethink this point though after I fully digest the new Hout & Fischer.
**** Your ex post explanation better speak to the (extensive) marginal fan and not just the intensity of hardcore fans, since my understanding is total number of football viewers is up, and so the explanation can’t be anything like the growth in fantasy leagues leads hardcore fans to watch 20 hours a week instead of 3 hours a week.
| Gabriel |
Like most native speakers of Stata, the most natural thing in the world is to start every script or session with a log file. Typing “log using” is like brushing your teeth, it’s the first thing you do and you just feel gross if you haven’t done it. Judging by what you get if you Google “logging in R” this seems to be something of a cultural eccentricity peculiar to Stata users as R users seems not to understand the question. In particular most responses to the question say something like “use sink(),” which ignores that to a Stata user a log file is neither the command history nor the output, but the two interpolated together so that you can see what command elicited what output.
However, much as the frustrated tourist abroad will occasionally find someone who understands what they mean in asking for a Western toilet, one great StackOverflow user speaks sufficient Stata to direct us to what we were hoping to find. Specifically, the library “TeachingDemos” includes a “txtStart()” function that behaves almost exactly like a Stata log file by default, but where you also have various options such as to suppress commands/output or to use Markdown format.
To install TeachingDemos:
Thereafter invoke it start a log file, do your work, and close it:
library(TeachingDemos) txtStart('mylogfile.txt') # this is similar to "log using mylogfile.txt" in Stata #insert code here to load your data, analyze it, etc txtStop() # this is similar to "log close" in Stata