I am an amateur in most of the fields that I enjoy commenting on in this blog. In my own field, I get as annoyed as anyone else when an ill-informed outsider buts in. Nevertheless, like Chesterton, I think amateurs ought to be allowed their say, especially since so many experts are demonstrably incompetent.
First, the wage growth data. This could be seen as a cautionary tale about over-reliance on averages. The average data doesn't look so hot, but that is masking interesting patterns in who is retiring, and who is coming back into the labor force. Even these latter numbers are still averages, but better, more informative ones. It is always worth asking yourself whether an average is the right tool to answer your question, when the metric of interest applies to an individual.
The next one is Kling's article on the broad economic statistics we all use to judge the health and success of our economy. Kling uses the term of art "legible", which seems popular today, but I would probably ask the same question in a different way: does GDP measure something real? Does it measure the same things through time? Do you have any way to verify this?
These are standard questions of data quality that apply to any effort to track and trend data over time. I'm most familiar with this in the context of quality control data, but I think the principles still apply for something as grand as macroeconomics. I especially like Kling's example that the computing power in an iPhone 7 would have been worth $12M USD in 1991. Does this really mean technological progress has made us all that much richer since 1991? I'm dubious this is true, which means that the stats are off in a major way.