When We Start Counting Again
Part Two of The Ultimate Gaslighting of an Entire Economy
In Part One, we named what is happening: a systematic erasure of economic and social reality designed to manufacture compliance while the K-shaped economy continues its quiet violence against the people at the bottom of the split. Not just the October CPI and the jobs report — but the food security surveys, the maternal mortality data, the HIV surveillance, the poverty calculations. Not just the tools a society uses to measure its economy, but the tools it uses to know whether its people are surviving at all.
We also met Sandy Smith, who spent four years reporting employment and unemployment data to the Department of Labor and is now seeing more wage garnishments and IRS levies in a single month than in fifteen years of visibility into that data. Sandy was told her reporting is no longer needed. That is the thread that connects everything: the systems designed to make suffering visible are being switched off at the exact moment the suffering is intensifying.
Now comes the harder question.
What do we actually do about it?
Can our system survive without accurate economic and social data, or are we already watching it fail in slow motion? What does a society look like when it has been running on a false signal for years? And depending on what happens between now and 2028, which version of the future are we actually building?
These are not rhetorical questions. They are the most practical questions we can ask right now. Because the answer determines whether the work we are doing, the conversations we are having, the communities we are building, matter at all.
The answer is yes. It matters enormously. And here is why.
We Have Been Here Before. It Didn’t End Well.
The closest historical parallel to what is happening right now in the United States is Argentina. And the story is worth knowing because it is not complicated. It is actually pretty simple, and it did not end well.
In the mid-2000s, the Argentine government was facing an election. Inflation was rising, and the official numbers made the government look bad. So instead of addressing the inflation, they pressured their statistical agency to report lower numbers. Career statisticians who pushed back were fired. The official inflation rate became whatever number the government preferred.
Ordinary Argentines kept trying to make good decisions with their money, not knowing the numbers they were relying on were false. Economists who tried to calculate the real inflation rate were hit with government lawsuits and heavy fines. It took a Harvard economist working safely from the United States — tracking grocery store prices online from outside the country — to show that real inflation was running two to three times higher than what the government was claiming. For years.
When reality finally caught up with the official story, it caught up all at once. Argentina has been dealing with the fallout ever since — repeated economic crises, waves of poverty, and a population that has learned not to trust its own government’s numbers. That kind of distrust, once established, is genuinely hard to undo.
Venezuela went further, suppressing not just economic data but health statistics — doctors were threatened if they included malnutrition diagnoses in medical records, even as millions were fleeing the country. The point is the same: once a government stops accurately measuring what is happening to its people, the problems it is avoiding do not go away. They grow. And the eventual reckoning is always harder than the truth would have been.
What Argentina and Venezuela tell us is not that the United States is destined for the same outcome. They tell us that data suppression is not a stable strategy. It is a delay. And the longer the delay, the higher the cost when the gap between the official story and lived reality finally closes. That is worth understanding now, while there is still time to make different choices.
What Would Actually Need to Happen
Let’s be concrete about the policy landscape, because it exists. The solutions are not mysteries. The obstacles are political, not technical.
In August 2025, after President Trump fired Bureau of Labor Statistics Commissioner Erika McEntarfer because he didn’t like a jobs report, Representative George Whitesides of California introduced the Statistical Agency Integrity and Independence Act. H.R. 4907 would do the following:
Restrict the President’s ability to fire the heads of the Census Bureau, BLS, National Center for Education Statistics, and Bureau of Justice Statistics except for cause, specifically proven inefficiency, neglect of duty, or malfeasance.
Explicitly prohibit removal based on “the substance, conclusions, or timing of any statistical data, report, or release prepared by the agency.” In other words: you cannot fire the person producing the numbers because you don’t like what the numbers say.
Severely limit White House power and authority over covered statistical agencies.
The bill currently has four Democratic cosponsors and is sitting in committee. It will go nowhere in the current House. That is the point.
Broader proposals from institutional reform advocates include:
Fixed terms for statistical agency heads that do not coincide with presidential terms, so that professional considerations rather than political ones drive appointments and removal. The National Academies of Sciences has explicitly recommended this as a structural protection.
Independent appropriations for statistical agencies, so that their budgets cannot be manipulated by parent departments as a tool of political pressure. An agency that has to beg for its operating budget from a politically hostile department can be starved into submission without a single public confrontation.
A nonpartisan independent oversight commission to audit federal statistical agencies, structured similarly to the Government Accountability Office. The American Statistical Association has advocated for real-time disclosure of data methodologies and revision processes.
Limits on political appointees at statistical agencies. Project 2025 explicitly proposed consolidating the BEA, Census Bureau, and BLS into a single agency under “strong political leadership” aligned with “conservative principles.” The legislative response to that blueprint would cap the number of political appointees and require that operational, statistical, and technical decisions remain with career civil servants.
International alignment with OECD standards for good statistical practice, which would create accountability to global norms that are harder to quietly abandon than domestic regulations.
Here is the reality: none of these reforms will pass a Republican-controlled House and Senate. They are in existence as blueprints for the moment the political landscape changes. They are infrastructure waiting to be built. The question is whether we will still have the memory and the capacity to build it when the opportunity arrives.
Because here is what is happening in parallel while these reform bills sit in committee: USDA has defunded the annual food security survey. The IRS Research division has lost 29% of its staff. All four advisory committees that provided outside expert oversight of the Census Bureau and BLS have been disbanded. The 2030 census preparation is already running behind. These are not reversible with a single piece of legislation. They require years of rebuilding, and you cannot rebuild what you no longer remember how to build.
Two Futures
Let’s name them plainly. Not as partisan fantasy in either direction, but as realistic scenario planning for people trying to make decisions in the present.
Scenario One: The 2026 Elections Shift Congressional Control
Democrats win back the House and/or Senate in November 2026. It is not impossible. The K-shaped economy continues to squeeze, delinquency rates keep rising, the placebo keeps losing its effectiveness as more people feel the gap between the official story and their lived reality. Historically, midterm elections punish the party in power during economic pain.
It is important to be clear about what Congressional control alone can and cannot do, because Trump would still be in the White House. Legislation requires a presidential signature, and any bill he opposes gets vetoed — and Democratic majorities from a midterm are unlikely to have the two-thirds needed to override. So the picture splits into two tiers.
What Congressional control enables on its own:
Hearings. A Democratic majority can subpoena documents, call agency officials to testify, and hold public hearings on what was destroyed during the shutdown. No presidential signature required. A formal accounting of what data was lost, what methodological compromises were made, and who made those decisions enters the congressional record — permanently.
A public blueprint. H.R. 4907 and its Senate companion can pass one or both chambers for the first time, creating a public record of Congressional intent and a ready-to-sign bill for whenever a cooperative president takes office. It will not become law under Trump. But getting it through Congress is itself a meaningful act.
Budget leverage. Appropriations are must-pass legislation. A Democratic Congress has real leverage in omnibus budget negotiations to restore some staffing and funding at BLS, Census, and BEA — not guaranteed, and subject to negotiation, but a genuine path that does not exist when both chambers are controlled by the opposing party.
What requires a cooperative president (meaning: 2028 or later):
Signing H.R. 4907 into law, creating a data restoration commission, fully restoring advisory committees, and locking in the structural protections for statistical agency independence. These require legislation that a president is willing to sign. They are the work of 2029 and beyond if the 2028 election goes differently.
What will not be possible regardless:
The missing data cannot be recovered.
Trust does not automatically restore. Even after Argentina’s government changed and more credible data began flowing again, it took years for confidence to stabilize. Once people understand they have been given false information by an institution they depended on, they do not simply resume trusting it because different people are in charge.
The structural inequality does not disappear with new data. The K-shaped split, the delinquency crisis, the wealth concentration — these predate this administration and are not products of the data suppression. They are what the data suppression was designed to conceal. Restoring accurate measurement reveals the crisis. It does not resolve it.
But here is what the 2026 elections make possible that nothing else does right now: accountability. The ability to put what happened on the record. The ability to build a legislative blueprint that is ready to move the moment the political window opens. The ability to say, with documented evidence, this is what the past four years actually cost the people at the bottom of the K. That accounting matters. It is the precondition for anything real that follows.
Scenario Two: Data Suppression Continues Through 2028
The 2026 elections do not shift control. The Republican majority holds. The Trump administration continues for two more years with the ability to shape, suppress, delay, or simply defund the federal statistical system.
What does American society actually look like at the end of that runway?
The answer is not speculative. We have historical models and we have trajectory data from right now. Here is what the research and precedent tell us.
The shadow economy expands. When official data loses credibility, private sector actors build their own. This is already happening. Investors are turning to satellite imagery of retail parking lots, blockchain-based supply chain tracking, and private consumption indices to substitute for BLS data they no longer trust. Some of this shadow data will be accurate. Much of it will be proprietary, expensive, and available only to those with the resources to pay for it. Information becomes another luxury good: the wealthy get accurate maps of the economy while everyone else navigates by rumor and feel.
The Federal Reserve operates increasingly blind. The Fed’s mandate requires it to balance employment and inflation. Without reliable data on either, its interest rate decisions become educated guesses. When those guesses are wrong, and in a fog they are more likely to be wrong, the cost is borne by every person with a mortgage, a car payment, or a small business loan. Jerome Powell already told us he was driving in the fog. Imagine four more years of fog, thickening.
International credibility erodes faster than most Americans expect. The dollar’s reserve currency status is not guaranteed. It rests on a global perception that American institutions are reliable, transparent, and governed by rule of law rather than political convenience. When Moody’s downgraded U.S. sovereign debt in May 2025, it cited concerns about fiscal governance. Sustained data suppression signals to international markets that the United States is moving toward the Argentina end of the spectrum, not the Germany end. Foreign investment slows. The cost of borrowing rises. The dollar continues its decline against major currencies. These are not partisan talking points. They are the logical consequence of institutional credibility loss, priced by markets that do not care about anyone’s political preferences.
The social contract frays at a pace that becomes difficult to reverse. Here is what concerns me most, and I want to be specific about why. A functioning society requires its members to believe that the rules governing economic life are roughly knowable and roughly fair. You can disagree about whether the rules are good. You can argue about redistribution, tax policy, the proper size of the safety net. But underlying all of those debates is an assumption that we are at least arguing about the same reality. When data is suppressed, that shared reality dissolves. And when people cannot trust official reality, they do not move to a rational alternative. They move to tribal epistemology: I believe the numbers that come from my side. I reject the numbers that come from yours. We are already deep into this territory. Four more years of manufactured fog will calcify it.
The people who suffer are not the ones building the shadow indexes. A small business owner in a low income zip code does not have access to satellite imagery of parking lots. She is making hiring decisions based on data she can no longer trust. The family deciding whether to refinance a mortgage does not have a team of economists building proprietary inflation models. The 55-year-old who lost her job during the shutdown and is now trying to figure out whether the labor market is improving has no alternative source to consult. The information asymmetry between the wealthy and everyone else, already vast, expands further. In a very real sense, economic data is a public good: it belongs to everyone, and its destruction harms the least resourced the most.
The Deeper Question: Does It Even Matter If the Truth Is Too Ugly to Fix?
I want to spend time here because I think this is the question that lives underneath all the others, and I think a lot of people are afraid to ask it out loud.
What if accurate data comes back, and what it shows is a structural inequality so vast and so entrenched that the political system cannot address it? What if the K-shaped split is already so deep that restoring the measurement doesn’t change the trajectory? What if the placebo, as harmful as it is, is the only thing keeping a certain kind of social peace?
These are serious questions. They deserve direct answers.
Suppression does not produce stability. It produces the illusion of stability while pressure builds underneath. Argentina didn’t achieve economic health by lying about inflation — it achieved a decade of deferred reckoning that wiped out ordinary people’s savings almost overnight.
Accurate data is a precondition for intervention, not a guarantee of it. You cannot design policy to address a crisis you have been told doesn’t exist. You cannot allocate resources to food insecurity you have stopped measuring. Accurate data does not automatically produce political will — but its absence makes political will impossible.
And a society with accurate data and political disagreement can at least argue from the same set of facts. A society without it ends up arguing about whether the facts are real. The data is not the destination. It is how we find our way there.
What We Can Do Right Now, Regardless of What the Government Does
I want to be clear that I am not writing this piece to produce despair or to suggest that we are passengers in a story being written by others. The institutional reforms matter, and we can and should support them. The 2026 elections matter, and we can pour ourselves into them. But between now and then, there are things we can do that do not depend on any of that.
Build local knowledge networks. The people in your community who lost jobs, skipped medical care, or quietly closed a business are data the federal government has stopped collecting. Document what you see. Share it. Community-level truth-telling is how the gap between the official story and lived reality gets named.
Support independent journalism and data institutions. The New York Fed, Yale Budget Lab, Brookings, the Center on Budget and Policy Priorities, and the Friends of the Bureau of Labor Statistics are producing and preserving accurate information under political pressure. Read them, fund them, and share what they publish.
Demand transparency from state governments — and push them to step up. Federal data agencies are not the only source of economic and social truth. States collect their own unemployment data, housing data, and health statistics. Many states have been more resistant to politicization than the federal government, and some are already stepping in to fill gaps the federal government has left behind. But most states have not yet made the commitment to expand and preserve their own data systems in a serious way. That needs to change.
Here is an under-appreciated opportunity in this moment: if the federal government is going to stop measuring hunger, maternal health, economic hardship, and disaster vulnerability, then the states that actually want to take care of their citizens will need to start measuring these things themselves. Not as a permanent replacement for federal data, but as a bridge. As a record. As evidence of what is actually happening to real people during the gap.
That comes with real challenges worth naming honestly. State data systems are not designed to be national substitutes. They use different methodologies, different definitions, different sample sizes. Comparing data across fifty states is messier than comparing national figures. Smaller states have fewer resources and less statistical capacity. And building new data infrastructure takes time and sustained political will that does not always survive the next election cycle.
But it can be done. Several states already have strong models for independent economic and health tracking. University research centers, state health departments, and nonpartisan policy institutes exist in most states and can expand their work. What is missing, more than anything, is the political decision to treat accurate information about how citizens are actually doing as a governing priority rather than a budget line to trim.
Something concrete you can do: find out what your state is currently collecting, whether funding for those systems is secure, and who your state-level representatives are on the committees that control those budgets. State data policy is unglamorous work. It rarely makes headlines. That is exactly why it tends to get cut quietly — and why citizen attention to it matters more than most people realize.
Talk about this with people who don’t already know. The most powerful thing that happened in Argentina — the thing that ultimately broke through the suppression — was not a government decision. It was the moment when enough ordinary people stopped believing the official numbers because their lived experience was too obviously different from what they were being told. That moment is approaching in the United States, and we can accelerate it by naming clearly what is happening. Not with rage, but with clarity. With the kind of calm, specific, documented truth-telling that is harder to dismiss than anger.
There is something genuinely hopeful in that. The tools of resistance here are not complicated or expensive. They are conversation, documentation, attention, and the simple refusal to pretend that what we are experiencing matches what we are being told we are experiencing. That is available to all of us, right now, regardless of what the federal government does next.
The gap between the official story and lived reality does not stay closed forever. The question is simply whether we are paying attention when it opens.
A Final Note on Why the Numbers Are Not the Point
I want to end where Part One ended, but go one layer deeper.
The numbers matter because the people behind them matter. Every data point in this fight is a person: the 55-year-old whose unemployment status was erased from the official record when the October report was canceled. The first-time homebuyer whose FHA loan is now three months past due. The twenty-eight-year-old whose student loan delinquency is now part of a 16.3% statistic she doesn’t even know she’s in. The mother whose birth complications will not appear in a federal mortality report because the staff who collected that data were placed on administrative leave. The family that is food insecure right now, in the middle of the largest-ever cuts to SNAP, in a year when the government deliberately stopped measuring hunger. The elderly man whose electric bill he can’t pay traces back to a federal program that was quietly eliminated — and who has no idea it ever existed.
When we fight to restore accurate economic and social data, we are not fighting for abstract policy quality. We are fighting for the right of those people to be seen. To be counted. To be part of a shared accounting of what is actually happening in this country, and therefore to be part of any conversation about what to do about it.
Invisibility is the condition the oligarchy needs to maintain.
We began Part One with a scene from a dystopian film that turns out to be real life. The Attorney General answering a question about justice for victims with a stock market number. The men in the towers, not seeing — or not caring to see — what is happening on the streets below.
Visibility is how we deny them that comfort. Accurate, documented, shared, undeniable visibility — economic and social, individual and collective.
That is the work. And it starts with refusing to look away.
***One more thing I want to say, as someone who has spent thirty years in financial planning. If you are not in the top 10% of income earners, this is the moment to become genuinely intentional about your financial life. Not afraid — intentional. Be thoughtful about what you spend and who you spend it with. Revisit your investment assumptions; the buy-and-hold strategies that served people well over the past few decades may not perform the same way in the environment being built right now. Know what you have, know what you need, and make decisions from awareness rather than either fear or false confidence. Your financial clarity is part of your resilience in this moment. (BTW - I am hosting an upcoming financial planning workshop and if you wish to join as my guest, reach out to me so I can get you on the list.)
Equal Stakes explores the intersection of personal financial empowerment and collective liberation. Part One of this series, The Ultimate Gaslighting of an Entire Economy, is available in the archive.
Sources and References
Argentina: Historical Precedent for Data Suppression
NPR / Planet Money. “Argentina Is an Example of What Happens When a Country Manipulates Inflation Data.” August 13, 2025. npr.org
NPR Illinois. “Argentina Is an Example of What Happens When a Country Manipulates Inflation Data.” August 13, 2025. nprillinois.org
The Science Survey. “Argentina’s Never-Ending Economic Crisis.” May 2025. thesciencesurvey.com
Financial Pipeline. “How Hyperinflation Took Hold in Argentina and Venezuela.” April 2024. financialpipeline.com
Venezuela: Data Suppression and Humanitarian Crisis
Wikipedia / Human Rights Watch citations. “Crisis in Venezuela.” Updated February 2026. en.wikipedia.org/wiki/Crisis_in_Venezuela
Legislation to Protect Statistical Agencies
The Census Project. “Statistical Agency Integrity and Independence Act: H.R. 4907.” January 15, 2026. thecensusproject.org
Rep. George Whitesides (CA-27). “Rep. George Whitesides Introduces Bill to Protect the Impartiality and Independence of Federal Statistical Agencies.” August 5, 2025. whitesides.house.gov
NPR. “A New Bill Could Help Protect the Census After Trump-Era Interference.” July 2022. npr.org
NPR. “Census Bill to Prevent Political Interference Passes U.S. House.” September 2022. npr.org
Threats to Federal Statistical System
Center on Budget and Policy Priorities. “Federal Data Are Disappearing as Statistical Agencies Face Budget Cuts and Political Pressure.” September 29, 2025. cbpp.org
Brookings Institution. “Around the Halls: The Cost of Compromising Federal Data.” December 2025. brookings.edu
Council of Professional Associations on Federal Statistics (COPAFS). “COPAFS Statement on the Administration’s Reaction to Benchmark Data Revisions from the BLS.” September 2025. copafs.org
Thurgood Marshall Institute / LDF. “Project 2025’s Threats to Voting Rights and Black Political Power” (covering Project 2025 statistical agency consolidation proposals). tminstituteldf.org
Principles for Statistical Agency Independence
National Academies of Sciences, Engineering, and Medicine. “Principle 4: Independence from Political and Other Undue External Influence.” Principles and Practices for a Federal Statistical Agency, Sixth Edition. 2017. nap.nationalacademies.org
Market Response to Data Integrity Concerns
AInvest. “U.S. Labor Data Reliability and the Shadow of Political Interference: A Looming Threat to Macroeconomic Stability.” August 7, 2025. ainvest.com
Foundational Data from Part One (Referenced in Scenario Analysis)
Mortgage Bankers Association. National Delinquency Survey, Q4 2025. February 12, 2026. mba.org
Federal Reserve Bank of New York. Household Debt and Credit Report, Q4 2025. newyorkfed.org
Moody’s Analytics / Mark Zandi. Consumer spending concentration analysis. September 2025.
Morgan Stanley. U.S. Dollar Devaluation Analysis. 2025. morganstanley.com