Statistical significance is not connected to real-world relevance.
With enough resources one could know the exact number without any margin of error. This number could however be the result of random fluctuations rather than systematic effects such as policies or natural phenomena. Only the latter are interesting, because you do not want to take decisions based on random noise. While some sources of noise can be eliminated, for example by polling more people, other types of noise are just there and are inherent of the process you are measuring. Wide confidence intervals also convey this kind of information, and more advanced statistical analyses can separate these two fundamental sources of noise. Those who care no doubt are informed.
Speaking of real-world relevance, there are about 159M people employed, so a confidence interval of 270k means that you can statistically detect changes larger than 0.17% within a month, and a CI of 70k after three months reveals changes of 0.04% or more. Since policy changes need time to propagate around the economy, at least one and perhaps two quarters, I would imagine that data for the immediately preceding month is not critical. Given the budget challenges in the last years, one could speculate that decision makers in the government were generally satisfied with this level of accuracy. And if they are not, sacking people does not change how statistics works.
Speaking of Trump: actions speak louder than words, and history remains a good teacher. I won't go any further since I am not American, I can only hope you guys get your shit together.
With enough resources one could know the exact number without any margin of error. This number could however be the result of random fluctuations rather than systematic effects such as policies or natural phenomena. Only the latter are interesting, because you do not want to take decisions based on random noise. While some sources of noise can be eliminated, for example by polling more people, other types of noise are just there and are inherent of the process you are measuring. Wide confidence intervals also convey this kind of information, and more advanced statistical analyses can separate these two fundamental sources of noise. Those who care no doubt are informed.
Speaking of real-world relevance, there are about 159M people employed, so a confidence interval of 270k means that you can statistically detect changes larger than 0.17% within a month, and a CI of 70k after three months reveals changes of 0.04% or more. Since policy changes need time to propagate around the economy, at least one and perhaps two quarters, I would imagine that data for the immediately preceding month is not critical. Given the budget challenges in the last years, one could speculate that decision makers in the government were generally satisfied with this level of accuracy. And if they are not, sacking people does not change how statistics works.
Speaking of Trump: actions speak louder than words, and history remains a good teacher. I won't go any further since I am not American, I can only hope you guys get your shit together.