Not sure that I agree here. I don't know about you, but my understanding of the variety of metrics they used in this article is quite minimal. Instead, it is instructive to just see the relative variation in the past five years or so compared to the 30 before that.
For instance, I have no idea what the metrics in Figs 2 and 3 are exactly, but I can see that the inequality metric in Figure 2 has reduced itself to approximately 1970 levels and that, since 1995, the welfare metric in Figure 3 has increased by (very roughly) twice the standard deviation of the past 30 years' measurements.
Of course scale is important, but it is folly to trot out the same argument every time a graph does not include the origin. Without knowing something about the y-axis variable we cannot make this type of claim.
I agree with you, kermit_de_fro, but it could be better. If the intent is to show relative changes, then it should show percentages or have a hard baseline that indicates "zero change".
I don't think "the bottom of the Y-axis isn't zero" is a guaranteed bad graph, especially considering some of the horrendous graphs out there. These ones are not that bad.
Suppose we want to show changes in temperature---unless you use the Kelvin scale, showing percentage changes is going to be bogus. Showing change relative to recent volatility seems useful.
If the meaning of the graphs isn't made clear, and the origin is not included (obscuring significance), it is not terribly unreasonably to suspect manipulation.
For instance, I have no idea what the metrics in Figs 2 and 3 are exactly, but I can see that the inequality metric in Figure 2 has reduced itself to approximately 1970 levels and that, since 1995, the welfare metric in Figure 3 has increased by (very roughly) twice the standard deviation of the past 30 years' measurements.
Of course scale is important, but it is folly to trot out the same argument every time a graph does not include the origin. Without knowing something about the y-axis variable we cannot make this type of claim.