The top-line summaries are definitely consistent with “waste.” Probably some of them have more nuance when you dig deeper, but does anyone disagree that there is not waste in the government?
Fraud and abuse are less clear. But it’s also difficult to ascertain the legitimacy of payments when they’re leaving treasury on checks with no memo or reference, and they’re compared to “do not pay” lists that lack frequent updates.
Here are some of my opinions, as someone who is mostly supportive of the effort but also realistic about its outcomes and risks:
1. The people voted for smaller government, and if the executive doesn’t have the power to reduce the size of its own bureaucracy, then there is no check on ever-expanding government. The executive must have full authority to examine all data produced by itself.
2. Federal spending on salary, agencies and operations is a drop in the bucket compared to entitlements and defense budget. Slashing jobs and even deleting entire agencies will not make a significant dent in the deficit. But if DOGE can really cut $1 trillion by end of year, it will have positive knock-on effects in the bond market.
3. Entitlements shouldn’t be treated with same bull-in-a-china shop approach as the current one towards agencies.
4. Social security probably has some fraud but I doubt it’s significant and is better resolved by identifying and punishing retroactively. Most of the “150 year old people” problems are exaggerated or outright wrong. However, it’s worrying that a system of age-based payouts has such uncertainty in its data.
5. It’s widely known there is significant fraud in Medicaid and Medicare. The true volume of this fraud is unknown and any effort to quantify it would be welcomed. But while fraudulent claims may be an issue, the real problem is unaccountable pricing of the healthcare system that allows for “legitimate” claims to cost more than any sane person would pay out of pocket.
6. In general, “if nothing breaks, you’re not cutting enough” is obviously true. But it does not follow that “things breaking” is an acceptable cost to pay. The approach needs to come with a well-defined rubric for evaluating not only “what to cut,” but also “which cuts to rollback.”
The data itself may have to be interpreted, which I would classify as 'suboptimal', but seemingly 'normal' for most projects I work with. I often have to join together various tables, remembering to include or exclude specific data via conditional logic. The conditional logic may be context-dependent, and documenting those cases is really key. Why include/exclude specific subsets of data to answer questions XYZ? Have those criteria changed over the years (and if so, why?)
Looking at raw data tables it's often quite easy to come up with ways to show the data to support whatever case you're trying to make.
https://bipartisanpolicy.org/explainer/immigration-social-se...
From a policy perspective making it harder for illegal immigrants to be employed might make it worth cracking down on this. But doing so would cost the government money both by preventing these payments into Social Security that don't have to be paid out and also the cost of the crackdown itself.