Evidence of Tightening During the Recession

I will show results from the R statistical language that will solidify some observations we can make about aggregate Nevada slot holds over time.  (Again the data covers the years 2004 - 2014 and comes from  http://gaming.unlv.edu/reports/nv_slot_hold.pdf).  Essentially what we want to do is figure out a regular pattern, subtract that and see what remains unexplained.

The blue line above is the average monthly hold in Nevada that I've talked about before.  The orange line is a standard time series estimate which we will take to be our model.  This estimated model “explains” roughly 70% of the variation of the data (as measured by adjusted R^2).  There are a few things we learn about the data in building this model.

First, a model looking backwards only two months works pretty well as far as capturing the oscillating pattern we see in the market overall.  If the data were weekly, I’d expect to see a relevant period of more than 4 but less than 10 weeks.

Second, there is a linear trend over time of increasing tightness: if you were to draw a straight line through the data, it would have an upward slant.

Third, December is a time of loosening: this explains the periodic low points about 12 months apart. 

Removing any of these three factors greatly reduces the explanatory power of the model.  But incorporating all of them into a one equation model gives us a powerful explanatory tool.  It may be a useful prediction tool as well, but that won’t be my focus here.  In the chart below I plot the errors of the model.

A model with no biases would look random and wouldn't have any discernible patterns.  This is mostly the case for our model except for the period corresponding to the recession, during which we see that the model systematically underestimates the tightening of slot machines.  This I think is strong first pass verification that there is something to investigate as far as concerns the dynamics between Players and Casinos during the recession.  Indeed, the "great tightening" was more than business as usual.

In my opinion this model is mostly useful for capturing descriptive qualities of the market and not necessarily useful for determining whether demand or supply side factors are the cause.  To further this line of analysis, I would apply the same form of model to the individual regions, and see if it retains its explanatory power.  The resulting cross section of variation will give us a lot of clues about why the patterns emerge.

After that, the goal will be to use economically fundamental variables, like income, profit and expenditures of the Players and Casinos, to explain a system of equations governing this list of variables as well as hold.