Methods" has a full page explaining the limitations of its data, including how non-sampling errors get made, from "misinterpretation of the questions" to "errors made in the estimations of missing data." Bottom line: To suggest that the input to the BLS data-collection system is precise and bias-free is -- well, let's just say, overstated. We know all of that and the informed user of the data understands monthly variability and ignores it. They examine longer-term trends, which tend to expunge these monthly variations from the data. Then Welch got down to using the data to see if he could decompose the change in the unemployment rate. But he didn't actually do that. He noted that "the labor-force participation rate in the U.S. dropped to 63.5%", which means there were "fewer people in the workforce" and that puts a downward force into unemployment given the other parameters. True. But he failed to mention that in September the participation rose again to 63.6 per cent adding workers to the labour force. He doesn't try to calculate what either movement meant for the final unemployment rate outcome. He then focused on the discrepancy between the payroll data estimate of employment change over August and September of 602,000 workers to the labour force survey estimate for September of 873,000 and concluded that: These three statistics -- the labor-force participation rate, the growth in government workers, and overall job growth, all multidecade records achieved over the past two months -- have to raise some eyebrows.