Recently, economist Anthony sharply criticized the monthly employment report from the U.S. Bureau of Labor Statistics, sparking widespread follow. As a nominee for the director of the Bureau of Labor Statistics, Anthony pointed out that the report has serious flaws that could mislead decision-makers.

Anthony emphasized that there are fundamental issues with the basic methods, economic models, and statistical assumptions of the monthly employment report. He believes that this data is often exaggerated and is, in fact, unreliable. This inaccuracy can have far-reaching effects on decision-making across all parties, from businesses to governments.

Notably, Anthony made a bold suggestion: the monthly employment report should be suspended until the issues are resolved. He stated, 'How can companies make reasonable plans when they cannot accurately understand changes in the labor market? How should the Federal Reserve formulate appropriate monetary policy?'

As an alternative, Anthony suggested continuing to release quarterly data. Although this data is not as timely as monthly reports, he believes its accuracy is higher and is more suitable as a basis for decision-making.

Anthony's perspective has sparked people's thoughts on the quality of economic data. In the current complex economic environment, accurate data is crucial for formulating effective policies. Whether it's Wall Street investors or Washington policymakers, reliable data support is needed.

This controversy also highlights the importance of economic data collection and analysis methods. As the economic structure continues to change, traditional statistical methods may need to be adjusted accordingly. Finding a balance between timeliness and accuracy will be an important issue that economic statistics will face in the future.

Overall, Anthony's perspective provides us with an opportunity to re-examine the quality of economic data. Before relying on this data to make significant decisions, it is particularly important to ensure its reliability and accuracy.