Cross Section of Nevada Slot Regions

Applying the aggregated Nevada time series model to the individual regions provides confirmation of the same general findings in the previous post.  We are also able to group regions by qualitative findings.

The following table suggest one possible interpretation using three qualitative groups.

The R^2 value is the amount of variation explained by our linear model.  Accordingly, within each group, I rank by the region’s R^2.  The higher the R^2, the better our model explained the actual data of the region.  The first thing to note is that the grouping is a pretty good indication of average explained variation.  So, what are the characteristics of each group?

Group 1:  All of these regions have characteristics that match the aggregated model.  All show a long run tightening hold of on average between 1 – 2.5 hundredths of a % per month.

Each member of Group 1 has a monthly oscillating pattern that can be described by two months of data. The average holds are pretty tight.  Finally all show a significant loosening in December.

Group 2:  Reno and Elko stand apart as they have on average a looser hold than their Group 1 counterparts, and show no long run change in monthly hold.  Instead of an oscillating pattern, movements in hold tend to reiterate themselves.  The December loosening is milder in these regions.

Group 3:  NSLT and Mesquite are the only regions that show a tightening in December.  This is most likely the result of the bad fit of the model.  With them SSLT shows a long run loosening in hold.  Their various other coefficients do not lead to any obvious interpretation.  The lack of competition in these regions (relative to the bigger gambling destinations) probably leads to different strategies, exposure to shocks and small sample problems.  An ARCH type model looks like it would be a better fit.

Importantly, the regions when analyzed under the aggregated model do not dispute recession hold tightening.  In fact most of the regional models, even Mesquite, show higher than average tightening during that time. Under the lens of the tightening hypothesis, Mesquite’s peculiarities are likely brought on by the recession.

As far as statistical methodology, there are still places I may have tripped.  Efficient estimators of the variance structure should be explored.  Also, since I ran the regressions one at a time, I could run a panel regression for better estimates.