Full Transcript: Eric Pachman on the Data the Fed Is Missing

Labor Force Decline, Medicaid Jobs, and the Coming Oil Squeeze

Matt: You’re watching Excess Returns, the channel that makes complex investing ideas simple enough to actually use, where better questions lead to better decisions. I’m Matt Zeigler, and today’s guest is the author and data nerd at Data For The People, like it says on his shirt, Eric Pachman.

Welcome back to Excess Returns.

Eric: Hey, thanks for having me. Great to be back.

Matt: You came on last call this past month. You did a segment on what the Fed is looking at when they’re talking about employment and inflation. I promised we would do this episode to go deeper into each, because the stuff you’ve been writing at Data For The People has been just on fire lately.

So we’re gonna do the deep dive today. You said, though, right before we recorded, you wanted to say thank you. You got a bunch of traffic, a bunch of people checking out the site.

Eric: Yeah. Yeah, it was almost kinda shocking. I was getting these, like, anomaly reports from Google and everything. The search traffic, like, you know, we’re a sleepy little site, building all organically, all word of mouth.

You know, bare bones to zero funding at this point in time, just doing the work ‘cause we love it. And, yeah, I mean, I was just on the tail end of your last podcast, like your weekly recap type thing, and all of a sudden it’s, like, you know, 60 people signed up for my distribution list.

And, you know, distribution list, that’s a heavy lift, right? Like, you have to actually go to the site, read the slate, click a button, put your email address in. I get it. That takes some commitment. And you already get something for nothing, so.

Matt: We have a listener base with gumption. We’ve got some gumption out there.

Eric: Oh, man.

Matt: And I’m telling you—

Eric: Well, I’m just very grateful.

Matt: I’m telling you, dear listener at home, make the man grateful. And you want this data, because this is where I’m starting us. We talked about the Fed, the way the Fed’s looking at the numbers. Eric thinks there are flaws and problems, not just with the numbers they’re looking at at the top level, but then as we drill down into their component parts.

So drawing on public data sets like BLS data and other places, he’ll give us sources as we go through these. This is not the arrangement that they’re looking at this data lens through. So if you’re running money, if you’re handling stuff with clients, you wanna see Data For The People and what he’s doing.

So I’m gonna ask you, very, very high level right now, I wanna lead with employment, I wanna lead with labor.

Eric: Yeah.

Matt: The employment trend in the US right now, is employment running up, down, sideways? What direction does it look like we’re heading?

Eric: Yeah. So I think that it’s actually, the—You phrased that question in exactly the right way, and we have a dashboard for that.

So if you go to Data For The People, we just released a brand-new dashboard where we take the Current Population Survey data, so this is the household survey, so just a little bit, like little aside here. You know, we get the employment report every month, moves the market one way or another. There are two surveys that are published here, hopefully most people know this.

The CES, that is the institutional survey. That is where the non-farm payroll comes from. And the CPS, that is the household survey. That is where the unemployment rate comes from. So those are separate. They sometimes will tell completely different stories because they’re totally different surveys.

One is surveying people, the other one is surveying businesses, right? Both the response rates are falling off a cliff right now, so there’s that, but that’s a whole nother discussion. So how much we trust them, eh, I don’t know. But they’re the best data that we have. So when I was with Bancreek, an asset manager, before I started Data For The People, we created a really good—I mean, it’s called the tree map, and go to bancreek.com, you can look at it.

And you can drill down into the non-farm payroll data. So if you see like, I don’t know what the last month was, it was like 50,000 change or whatever, that’s what is called at the BLS hierarchy, level zero. Highest level. And then when the number gets higher, you go down to more granular levels until you get to like sewing machine fabricators or whatever, down at level seven.

So you can see a lot of detail on all the industries. That’s already there at Bancreek. That’s the CES. That’s the survey of businesses, right? Non-farm payroll data. So the problem with the CPS data, and again, sorry for all the detail, but I think this is really important. Because here’s the thing—

Matt: This is really important because these surveys, how the surveys are being responded to, how the information’s being captured is not the headline number, and that’s why I wanted to unpack this, so keep going.

Eric: No, no. And so, and it will also, like if you can see this data, which this is the challenge, like the BLS. And look, I’m not trying to hate on them, but their job is not to make you see the data. If you look at the release from the BLS from last month, the press release, it’s like unemployment unchanged.

Unemployment for Black people, unemployment for this, unchanged. It’s like, great, your entire story is that there’s no story, and then it’s like, “Oh, and by the way, the labor force participation rate fell to 61.5%. That was down .4 points.” And I’m like, “What the...” And then you’re just like, “Moving on.” And you’re just like, “Whoa, whoa, whoa, whoa.

Time out.” Like, I’m a storyteller. You lead with the crisis in the labor force participation rate first, rather than like, “There’s no change in the unemployment rate.” But this is the issue with the BLS right now, and this is the issue with the Fed. It’s like you have to go back and like, look, ask Claude. Go back and study the history of how these different benchmarks came into place.

And there was a comment on that last video. I wanna address this comment. It was like, “You’re telling me that the Fed doesn’t have access to all these tools?” Of course, they have access to all these tools. They know all the minute detail. But they can’t all of a sudden come out and say, like, “For the last 30 years, we’ve been focusing on the unemployment rate, and guess what?

That no longer works. The world has changed.” Like, they’ve just kind of painted themselves into a corner to say the unemployment rate is the one ring that rules them all. And right now, I can tell you, investor person that cares about America, you will not see the recession coming with the unemployment rate.

It’s already in the data, the depression, the recession, the crisis. Let’s call it the labor crisis. It could be like it’s an inflationary surge because we just don’t have enough people to work. But if you go to Data For The People and you look at our latest data visualization, which takes almost all the data in the CPS survey and creates a drill-down tool to where you can look at every dimension.

Forget about the unemployment rate. That’s in there too for you to look at it and see that nothing’s happening. Go look at the people that are not in the labor force right now. You can actually see, and we just wrote about this, the revisions that are happening as the BLS improves their model and the census improves their model, and you can see the number of people that are working age people just disappear.

And so you’re just like, “Well, wait a second. Where are they going?” Well, they’re 75 plus now. And it’s like, well, the actual age of people didn’t change, but the whole BLS and the whole census runs on models, and we just wrote this. There’s this great quote, “All models are wrong. Some are useful.” Well, they just made their model a little more useful.

It’s still wrong. But now all of our projections going forward have less working people to pay taxes, to pay into Social Security, to pay into Medicare. This goes way beyond investing. And I’m not here to tell you, like, what to believe in it. I’m here to tell you the tool is there. And so you wanna answer your question on the number employed people, just go select the series that says employed and you’ll see it.

And then select it by race, select it by ethnicity, Hispanic, Latino. Select it by sex. Select it by veteran status. Do it all. I mean, it’s all there. By the way, the veterans one is crazy. Like, the veterans are falling off a cliff. Like, we’re just, we’re not... I mean, this is well-known, but I just learned it.

It’s like, oh, wow, you know. Clearly, a lot of the Vietnam era, Gulf War era, they’re all dying off and retiring out, but they’re not being replaced. So it’s like, where are all the people that are fighting for our country? They’re not there anymore. Anyway, that’s an aside. But, like, all the data is there.

Matt: Can we get a slide up for—let’s look at beyond the unemployment rate, because this is part of what we’re dancing around now. So let’s talk about this. What’s going on here?

Eric: Yeah. So, okay, when you pull it up, it will come up to age 16 years and over civilian labor force. So I think it’s very, very important if you understand how cities work to focus on the civilian labor force, because that is the number of bodies that create tax revenue.

That is the number of bodies that can actually go out and shop for things, support businesses. Until we come up with a mechanism to tax bots, AI, and massively tax big tech, which, like, I’m not holding my breath. Like, this is the business model of the US, right? We need people to work, and so that’s why you have to look at the labor force. So right now you see this long-term trend going all the way back to 1950s for 16 years and over. But now just go through and, like, there are literally 30 different dimensions and cuts that you can look at in here. You gotta spend a little bit of time with this and really have the desire to be educated here.

So just go in and look at, I’m gonna look at the number of 45 years and over people. Okay. Then that pulls up what’s called a non-seasonally adjusted chart with the 12-month average on that in the civilian labor force. Well, now what if I’m concerned about or if I’m interested in the 45 years and over, but just the labor force participation rate?

Then you’re like, “Uh-oh, wait. What happened here?” So in 2009, that was at 55.9%, and now the 12-month average is down to 50.7, and it is falling off a cliff. And by the way, I haven’t even looked at this chart before. There are too many dimensions in here to look at. But now, all of a sudden, since what happened in January was this whole, like, reshuffling of the models, the labor force participation rate is really, really dropping fast for the 45 years and over.

It’s down to 49.6%. So then you could say, “Well, what about men?” Oh, well, so men, oh, boy. That chart is death. So men is down to 54.7%, the lowest level by far on record. The prior minimum was back in the 1990s where it was 57.5. It went all the way up to 62.9. Women, well, they’re much better, which this actually jives with the piece that we just worked about.

Women are the driver of our labor force. We have to thank them. If you’re a man, go out and thank the next woman that you see for supporting this labor force and helping it to grow. And if you don’t believe me, spend even five minutes working through this database to see that men are not participating at an increasing rate and women are participating at an increasing rate, which we can go into.

That has a lot to do with which industries are the driver of our labor force expansion and employment just in general.

Matt: So let’s take it there next. Another part that’s been fascinating is as we look at those jobs that are coming out, many of which in the 45-plus crowd, so these are the people you know.

These are my brethren. These are my peers. These are the ones who are making the six-figure salary, doing some job. Those are the ones that are going away right now. The weird part that’s stabilizing the number in employment right now is the other jobs that are being added, and they’re not that six-figure, white collar, go out and do something because you’re 45 with a college degree job. They’re coming in in what you’re calling the Medicaid care economy, and you’ve got some insane charts explaining why, ‘cause you’ve been talking about this for two years. Healthcare is the driving place, and this Medicaid part of it is huge. Let’s get some more charts up.

Eric: Yeah. So I wish I remembered all these stats right off the top of my head, but you can go to...

Well, let me step back. So this has been about a year and a half in the making. So there is a visualization on our website called Medicaid Care Economy Concentration of State Job Growth. So back when I was at Bancreek, you know, my background’s in healthcare, and so I’m looking at these healthcare job growth numbers, and it’s, like, 60% of total payroll, 70%, 80%.

By the time we got to the end of 2025, it was, like, I don’t know, the numbers are in my reports, but it was something like 2 to 3, 400% of all job growth was coming in healthcare. Everything else was contracting. Wall Street Journal covered this. Everybody knew it by that point in time. But what they didn’t know, because people don’t tend to drill down like we do, is they didn’t know where those jobs were coming from.

And so people are very confused about, well, is this all administrative oversight because of how inefficient our care economy is? Is it actual doctors? By the way, no, it’s not doctor growth. Is it nurses? Yes, it’s nurses growth. We can show you that in a visualization we have. But overwhelmingly, this growth is coming from what’s called social assistance, and within that, individual and family services, and within that, services for the elderly and disabled and home healthcare aides.

And so what is that? That is, you know, I have an elderly parent or grandparent, they don’t need to be institutionalized yet, which would be very costly for me and/or the state. And so you can drop them off at an elderly daycare facility. They can, you know, keep track of their meds, they’ll have socialization, you can work your job.

It’s a win-win, right? Or what we more commonly know is you can hire someone to come into your home to take care of your parent or your grandparent. Those people, by the way, we have another data visualization, which hopefully you’ll put up, which shows you what everybody makes. 830 professions across this country by city.

If you go and explore that, you’ll see that these are some of the most underpaid people really in the entire economy, and is the engine of job growth. We wrote another piece on that, which I’ll give to you to put in the show notes, but it basically is like we’ve created a couple million jobs in this over the past, like, decade or so.

And so our aging of the economy, which I think most people know, the boomers sort of rolled over into the 65 plus like in the middle of the 2010s. That has created huge demand for people to take care of them. By the way, most of them are women. I think it’s like 80% are women, something like that, and about 30% to 40%, depending on the study, are immigrants.

So there’s another issue there with maybe a potential supply crunch with the people to take care of them. Anyway, all that said, I’m staring at this for like a year and I was like, uh, then the one big beautiful bill hit, right? So what’s that gonna do? Well, it’s cutting Medicaid by a trillion dollars over 10 years.

And as putting my investor hat on, I’m like, “Okay, we need jobs to keep growing. We need people to take care of old people to keep growing those jobs so the Fed says, ‘Oh, the job growth is healthy.’” And by the way, what I happen to know is that most of the home healthcare aides, the primary funder for them is Medicaid.

And then, you know, Trump in his infinite wisdom, and I’m not being like political here, I’m just saying that he probably doesn’t understand the way this works, he decided to cut this, or the administration decided to cut funding for this, which is basically the major growth driver of our jobs in our...

And, look, it’d be probably not advised very well. But Medicaid is a state-based program, and so you can’t really understand what’s going to happen unless you drill down into the state. And so that’s what I did. I went down into what’s called the Quarterly Census of Employment and Wages data. That is, by the way, one of the most valuable databases if you wanna understand anything about job growth.

It is based on unemployment insurance claims or unemployment insurance reports from states. It covers 98% of all W-2 employees. It is not a model. It is the only real source of data that we really have at the BLS. It comes out, like, six to nine months in arrears, so a lot of investors don’t use it. But my gosh, like, you can actually get the individual industry down to the individual county.

And so I’ve used this database for a lot of things, for a lot of the stories of America that I tell. But as an investor, especially with AI, there’s no excuse. You should be using this database as well, or at least reading my stuff ‘cause I use it a lot. So that’s where this data visualization came from.

You can basically look over time, and you can actually press this little play button in the window end quarter and then just see how much job growth came from what’s called the Medicaid care economy. So this includes assisted living facilities, it includes nursing homes, that kind of stuff. How much job growth as a percentage of all the job growth in that state over a one-year period, a two-year period, and a three-year period?

And what you’ll find is that that map gets increasingly more red. And now we’re at a point where through the end of 2025, which is all the data we have, in that one-year period, like, I think it’s, like, 32, 33 states would’ve had negative job growth if it wasn’t for Medicaid care economy. And then think of that. Setting up into the beginning of 2027 is when most of those cuts start in Medicaid.

And so this is something that every investor needs to at least have on the back of their mind as like, this is a major tail risk. Now, maybe it’s a tail risk to the upside because if all of a sudden we have no jobs, then people just care about rates getting cut, and then everyone gets really excited about more speculation.

I can’t tell you which way the market’s gonna go. All this helps is saying that there’s a major tail risk that’s out there, and I helped you quantify it with this, that is going to impact the real job market. And if you have a parent or a grandparent that relies in any way on a home healthcare aide, you better figure this out right now, and figure out where all the money is coming, what staffing agency it’s coming through, because that could all of a sudden just disappear depending on which state you live in.

Matt: It all ties back to consumption. It all ties back to real growth in the economy. I wanna hit one more part on employment before we start getting into the cost side of this and talking about inflation. I wanna talk about the wage ledger, because I think this is another fantastic data series.

Eric: Yeah. So this one, if you actually go to the wage ledger, I’d love if you do that because I am the most proud of this one, not because it is the most involved, the most complicated. In fact, there is a spreadsheet that lives out on the BLS website. It’s called OEWS, Occupational Employment and Wage Statistics.

Everybody should look at it if you care about, you know, how much people make. You know, I’m sure that there’s some investing thesis for knowing that kind of stuff and how that’s changed over time. The problem is, is the spreadsheet is, like, largely unusable in Excel. It crashes, it’s hard to filter. And so all we did here was take that and put it into an interactive data visualization so you can, you know, sort through that and sift through it and learn from it.

And not only that, but the main reason I’m proud about it is that you’ll see the author of this is a gentleman by the name of Jonathan Pickens. He is a rising senior in high school. And so I am working with him. He’s one of my three data storytelling fellows that we have at Data For The People, and this is kind of a work in progress project.

He’s doing a really big project, which I’m sure after we publish this, you’re gonna wanna talk about it again because it’s evaluating the changing cost benefit of a four-year college degree over time versus a trade career, which is very complex. But as he’s building the databases and getting to learn all these databases, he’s coming up with these interactive tools that on their own are very, very useful.

And so this wage ledger is... I thought was fantastic that he came up with. You can basically go through 830 different jobs that are shown, sort them from high to low on the annual median. What will come up is the number one paying in the country. By the way, this is only W-2 employees, so you know you’re not gonna find Elon Musk on here or any people that own businesses.

Pediatric surgeons make a median salary of $559,000. There are 1,190 of them. But then what you can actually do is sort that by employment. Boom, what comes to the top? Home health and personal care aides, 4,305,810 making an hourly median of $17.21, $35,800 a year. The pay range, you can even hover over that pay range.

You can see that it is very tight. The 90th percentile makes $45,000 a year, which by the way, if you go to another one of our data visualizations you will find in some of the higher cost areas, that still doesn’t cover the cost of poverty to raise a family of four. So we are building basically all of our job growth and betting it all on people that are largely women, largely immigrants, largely living at or below the poverty line to support a family of four.

And this is where we come back to the Fed to make it full circle. The Fed is report—They’re not telling us about any of this. So do they know it? Probably. But this is a political game, right? Why are they not telling us that the quality of the job growth is coming all from home healthcare and personal care aides that make $35,000 a year?

Like, these aren’t jobs that are creating tremendous disposable income for average Americans. That is an important data point I would think we would want to have if we were claiming it is a strong or robust job market. But we’re not getting any of that information. And shame on—Sorry, I’m gonna say it.

Shame on the people that are interviewing them and interviewing the, whatever the guy’s name is, the chair of the Fed, this new dude. Shame on them for not asking these questions. I mean, like I really can’t believe that the people that are invited to the room don’t have access to any of this data.

The people at Bloomberg, the people at Barron’s, wherever they are, whoever’s coming there, they don’t have data analysts that can do this? I just had a high schooler do this. So don’t tell me you don’t have the chops to do this, all right? I would love to be in that room and ask some questions, by the way.

I would love to see what the answers are, because then we’d actually get to figure out, does he really know this, or does he not even know what we’re seeing here? Because this is the level of detail that I think investors really need to know. But right now, it’s just a game of like, your investors that are listening to this are gonna say, “Oh, wow, now I know this.”

But like, you know, Ben Hunt says, if this is knowledge that only investors on this podcast have, but they know that not everyone else knows this, then the game of investing is to really figure out, well, what does the consensus know? And if the consensus doesn’t know about this, does it even make sense for me to act on it?

Because the real economy is gonna suffer. We know this from the data, right? All the data says that. You can triangulate any which way. But if no one ever figures it out or it takes two years, what are your clients gonna say? Like, you gonna sit on the sidelines waiting for that? It’s a very hard job, this job that you guys have.

Thankfully, I don’t have to do it anymore. I just have to diagnose all this, and you figure out what to do with it.

Matt: You found a good place. And if I get Warsh on speed dial, you’re gonna be one of the first ones I get to know. I wanna take us to inflation next. I wanna go to the cost side.

And the reason I wanna go there is because this is another data series that’s enormously clunky, enormously funny in the way that we even talk about it or measure it. So I’ll ask the same question that I did about labor to lead off with. Inflation as we understand it, at the top, top level, up, down, sideways?

Where is inflation moving right now?

Eric: Oh, up. Up, for sure. Up. Unambiguously. That one’s an easy one to tell you. Like, you don’t even have to do all the work that you’re doing on the job side to be like, “Well, wait a second. It’s this, the not in labor force, the participation rate,” like all these things that people don’t talk about.

You gotta drill a little bit for that. Inflation is just like, just look at the data. I mean, like, we know that it’s up, but we published about two years ago a data visualization on Bancreek, bancreek.com. It’s free. It’s the first one we ever published on CPI. We followed up with a PCE one. And all it does is it takes the underlying kind of items, about 180 mutually exclusive items, and it will size them and show you, like, this is the impact that this is having on inflation.

Matt: So just like you did with CES and CPS, just take a second and talk about CPI, PCE, how you guys broke that down to show it, because people need this reminder.

Eric: Yeah. Okay. So CPI is, you know, surveyed, measured by the BLS. It is supposed to be the consumer’s experience of inflation, and so the weights are different from PCE because that is, like, the broader economy’s experience of inflation.

So, you know, each of them have different weights. They have different ways that they measure things. So when you drill into PCE, several of the items will actually be taken from CPI, and they’ll be the same, and then others will not. They’ll be taken from PPI, you know? And so it’s this mishmash of them, but the best example I can give you with PCE, and given that it is, like, the holistic view of the economy’s experience of inflation, is it has, like, a much higher weight for healthcare, because you have employers, you have the federal government, Medicaid.

Like, you have a lot of non-consumer payers. It’s mostly non-consumer payers within healthcare, and so you’ll see a much larger weight there. And then you see a much smaller weight on shelter. So, you know, PCE is, the Fed says it’s what they look at over CPI. The Fed also says they look at core, right?

I have been on record and written multiple times about how core is, pardon my French, bullshit, because core was defined, and you can do the research on your own, by coming out of the 1973 oil shock or whatever, and then it was having impacts on food prices, and the current Fed chair at that time was like, “Well, this is noisy, and so let’s strip it out.”

And so they stripped it out, and, like, we haven’t revisited that ever since. And I wrote a piece—and I can’t remember exactly where this was but trust me, I wrote a piece—that actually looked at the volatility of these categories, and it’s like, okay, gasoline’s really volatile. Makes sense to strip that out if you are really looking to smooth this out.

Still a really important, you know, variable for the consumer, so we probably do care about that a lot. But food is not variable. Like, it’s not nearly as volatile as healthcare. And so it’s pretty arbitrary the way that core is measured right now. If you were just doing it based on volatility, you would strip out all of healthcare, and you would include all the groceries.

And then if you were really building a benchmark that you wanted to measure the pain and the suffering of the average American, you would measure gasoline and groceries first and foremost because that’s what we feel and that’s what we experience, you know? The surveys themselves have all sorts of assumptions baked in.

CPI is heavily influenced by shelter, and the number one item by weight is something called OER, Owners’ Equivalent Rent of Residences. It itself is a proxy. It’s a fabricated surveyed number that is trying to come up with kind of an estimate of what rent would be and the changes in rental from month to month for people that own their homes.

So they literally just place a call to you. I don’t know if anyone who’s listening has ever got this call. I haven’t. They place a call and they’re like, “Hey, what would you rent your house for right now if you could, theoretically, hypothetically? What would you do?” I’d just go to Zillow and be like, “I don’t know.

I mean, like, what does Zillow say?” And so then that’s what they—I’m assuming that’s what people do, and then that is 30%. That’s about 26% to 27% of all of CPI is just on that. And so why did CPI go up so much in 2022? It’s just because shelter was going up so much. This one item was. And why is it, like, staying muted now?

Because shelter’s staying muted now. But when you look underneath that, and we published a report on Bancreek, I think something like 42% to 45% of all items out of 180 have breached one standard deviation over the historical mean, so they’ve moved into, ooh, this is anomalous, you know? And you also have, like, a huge amount that are above two standard deviations.

And so you can see this real easily on that tool. You just hover over them, and you can just all of a sudden see a bunch of stuff like spiking. Gardening, lawn care services, beef, coffee, like random stuff like hair care. I don’t know, like it’s weird stuff that is just kinda all going kinda parabolic.

We did that report on Bancreek, and I thought that was a really good one just because it’s like no one’s talking about any of this stuff. The weights are so small that you really don’t care about your laundry care services that are spiking. But it’s like all of a sudden you put all of them together and you’re like, none of these things actually are related, and yet they’re all spiking.

That doesn’t feel so good. And that’s free. You can see that very easily in our tool.

Matt: So one of the places that you’ve been drilling in that I think is the most valuable, and certainly this came up when we were recording that last call a week or so ago, was looking at oil. And you’ve got some charts on the petroleum inventory seasonality that I think are fascinating, especially where we are with the Strait of Hormuz and our on-again, off-again war, and the 3-2-1 crack spreads.

I think these are really, really useful to understand right now, even for the people who aren’t oil investors or aren’t tied to that market. Everyone’s an oil investor now. This cost flows, it flows through to everything.

Eric: Everyone needs to become an oil investor to be an equity investor. That’s what I think. So let’s start now.

Matt: All right, let’s start now. Petroleum inventory seasonality. What’s going on there? This comes straight out of your background. We should call this out too.

Eric: This is a new thing. And let me give you a bit of context and background. So I have for years, I’m a chemical engineer. I worked at ExxonMobil. I modeled refineries. I know this shit, right? I tried to forget it. I can’t. It’s been tattooed in my brain how crude oil gets processed through a refinery. I have been trying to come up with a way, I like speaking in terms of analogies, metaphors, whatever, to explain oil to people that they’ll understand.

Like, I don’t know, like at the level of my 11-year-old where he gets it, right? Because I think people think that oil is one thing. Crude oil, oh, we have lots of crude oil in this country. We’re producing record crude oil. We’d have no problem. People who will go unnamed are saying that, and people probably are just believing that.

Yet, let’s look at the evidence. We’re exporting record amounts of oil, still importing a lot of oil, and you’re like, and then we’re drawing down our strategic petroleum reserves to the lowest level in like 45 years, like almost on record we’re getting close to that. You know, the oil inventories when we look at those charts, which we’ll talk about, are just all crashing.

And you’re like, “Why would you export your oil?” If we’re out of oil. One would think that, like, if we had any strategy whatsoever, and rather than the market or us basically just selling this to the highest bidder, which that could be it, is like nobody’s at the wheel right now. And so of course, like, if I have oil and I’m a company and I own it, and I can get a higher price by selling it on the market, and I’m not forced to send it to a refinery in, you know, Pennsylvania to basically say, like, “Well, we wanna bring gas prices down in the US,” then that’s what I’m gonna do.

Like, if no one told me to do it. And so that’s one part of it. But the other part of it is that oil is not oil. Oil, and I actually have, by the time this comes out hopefully it’s out, but I should have an op-ed coming out in a major national publication. So that will be posted on Data For The People. And as soon as it’s out—

Matt: We’ll get a link to it. Look in the description. If it’s out when this is out, it’s in the description.

Eric: Awesome. Awesome.

Matt: So go on. Keep going.

Eric: So I have an analogy in there that I finally think can work, and so we need to tell everybody about this analogy. Oil... Think of oil as fruit, or even better, a fruit salad.

So everybody knows that if you order a fruit salad, it’s gonna have cantaloupe and it’s gonna have honeydew and it’s gonna have blueberries, it’s gonna have strawberries, it’s got apples. It’s gonna have a mix of all the different types of fruit. Oil is not blueberries. Oil is not one type of fruit. It is a blend of all the different types of fruits, which are really hydrocarbons.

So there’s some fruit which creates propane, and there’s some fruit which creates gasoline, the ones with six hydrocarbons, or the ones with six carbons or eight carbons or something like that. There’s some fruit that creates diesel, some fruit that creates jet fuel, asphalt, petrochemicals, all that kind of stuff.

And so every type of crude oil is different. The type that you drill in the Middle East, that’s where most of the oil has come from over the history of our world. And so most of the refineries, which we haven’t built a new refinery here in, like, probably my lifetime, most refineries were designed to produce that kind of stuff, which is heavier.

It has more of the diesel in it. It has more of the jet fuel in it. It has more of, like, the heating oil, more of the heavy stuff. So refineries develop technology called fluid catalytic crackers and cokers to take the heavy crap in the oil, billions of dollars of technology, and crack that and morph it chemically and physically into gasoline.

Now, the stuff that we’re drilling here, which is very recent, right? This happened in, like, the 2005, 2006, the fracking revolution, all that kind of stuff, the shale oil, all that. This is very light oil. Lots of the gasoline molecules in it, not a lot of the other stuff in it, right? Well, now, if you take that and you put it into a refinery, there are actual physical limitations of, like, what that refinery can do.

In the entire refinery, the economics are managed to, like, maximize the economics, right? So you wanna maximize the yields. There are specs on every product. I mean, it’s very, very complicated. And I built refinery models to optimize all of this based on what type of crude. And I can tell you that a refinery on the Gulf Coast, you would never send.

You’d never be like, “Oh, I’m gonna take all the oil from the Permian Basin, which is literally right there, and send it all here,” because all of a sudden, the yields of crap that comes out the other end, it’s all broken. It’s not what the refiner wants to maximize their profitability. And so what happens when you have the wrong type of oil matched to the wrong refinery?

The crack spreads rise. And so the crack spreads is the market telling you this is three barrels of... It’s a proxy for refining margins. So it’s three barrels of oil equals two barrels of gasoline and one barrel of diesel. All three of them are separately traded products on the market. They all are just like stocks, right?

You know, nobody is fixing these prices. Nobody’s controlling this. The refiners get what they get from these prices. And what’s happening is when oil gets mismatched to the refineries, the economics of the refineries are bad. Now, if you have what’s called a hydro-skimming refinery, which is like actually one of the cheapest type of refineries that wants to process like light sweet crude that we produce, man, you’re a cash machine right now.

You could just run that thing flat out, make tons of money, $60 a barrel in crack spread, which is four to five times your historical profit margin. You’re making 400% to 500% profit. That’s why refining stocks are probably up. I don’t know, I don’t check them, but my guess is they are. But if you’re like that Gulf Coast refinery, the big, the bad refineries, the Exxon refineries, the BP, the Shell, that’s not the kind of oil you want.

And so what I wrote in this op-ed is we close the strait, we open the strait. When you close the strait, all the flows across the country, or the world, get disrupted. The wrong oil goes to the wrong place, and all the economics are screwed up. This is COVID. When we closed the strait, we created COVID for oil markets, right?

When we had COVID, remember what it did to all the supply chains for like two, three, four years? But we weren’t back, like wearing masks in public. I mean, there wasn’t any immediate near-term threat after we realized we needed to mask and we had vaccines, but it still took years for supply chains to recover.

Like, you don’t even need to know about refineries. You just need to know that we just shut down the bottleneck of the key choke point. We shut down Atlanta Hartsfield, if you think about this from, like, the air traffic network, for, like, two months. I mean, don’t tell me that not every single flight around this country will be affected eventually.

Maybe not on day one, but it takes a long time. And the air traffic network is underselling it. Like, that’s actually a lot easier to reset because you just don’t fly overnight. Whereas, I mean, think about all the ships that are sailing around the Cape, sailing all these, like, extended voyages to not pass through the strait and everything.

It’ll take months for those to actually get back to where they need to be. And then we just keep shutting it down and then opening and shutting it down, and the insurance premiums are high. Like, arguably, this may never go back to where it is. Especially if Iran is able to formalize the PGSC. They start charging, you know, fees on this.

The capacity is, like, permanently lower because we clearly don’t want that to happen. All bets are off. Like, we just created COVID for the oil markets from a supply chain standpoint. We’re seeing it in the inventory visualization that I put together which, by the way, this is yet another example of the government not giving you the data that you really should have.

They tell you, “What was the percent change versus the last five years?” And then you’re like, “Oh, diesel inventories are down 10% versus the last five years.” You’re like, “10% isn’t the scariest number ever.” And then you’re like, “Well, wait a second. But in 2022, we had the Russia-Ukraine thing, and then, like, everything was going crazy back then.

Oil was, like, at 100-plus. You know, gasoline prices were at $6 average. That’s one of the five years I’m comparing it against, the worst year on record.” Why wouldn’t we compare this against all 40-plus years of history? I don’t, it doesn’t make any sense to me, and that’s why I did it. So you can actually go and look at the diesel inventory chart, the gasoline, the Strategic Petroleum Reserve, crude oil, and you can look at it against all history.

And you can click on and off of different decades. So what if you don’t wanna compare it to the ‘90s or the 2000s? Just click those off, and then it will take those off the charts, and then you can actually see how bad things really are. And it’s scary. It’s scary bad. Like, if inventories matter at all, this is COVID happening in real time, and the investing public couldn’t care less.

Like, it’s like COVID without the transmissibility until it hits. And then, like, my worst case, which we’re heading towards, and I think a lot of oil analysts are talking about this, is, like, one day you’ll show up at the gas station and you just won’t be there. Or what happens when, you know, El Niño hits?

What happens when hurricane season comes through and one of them happens to take out a refinery in Louisiana? I mean, like, we’re basically just, like, sacrificing all of our risk mitigation for the sake of whatever. I mean, short-term profiteering from the administration, from the government, from investors, like we’re pulling forward all of the gains.

So go party while you can, but like, I mean, like I look at this and as a knowledgeable, not investor, but like concerned citizen that happens to know how this all works, and I’m like, “I better prepare. You know, I better prepare my family for this. I better just get prepared for times to get very difficult.”

Maybe we end up threading that needle somehow. I don’t know. I can’t tell you what’s gonna happen. I can just give you a probabilistic assessment of it, and it is not pretty right now. Don’t take my word for it. Look at the charts.

Matt: Tie that back to CPI, to PCE, the way that most people are looking at this, because I think what you’re highlighting, that’s especially important, is the tail risk this represents if there’s overlapping events. So this helps put applied pressure that’s not going away onto the inflation numbers across the board.

On top of that, though, how much is this showing up in CPI and PCE now versus in that tail scenario, how much more does it move those numbers where the Fed actually looks at this and says, “We have an inflation problem”?

Eric: Yeah, so, oh man, how do I say this kind of like somewhat politely? So let me be honest with you. Like, I haven’t really looked at PCE in a while. So, but PCE is the same as CPI, just with different weights. You know, go look at it yourself. Ask Claude. They’ll give you all the weights, you know. So like one weight will be higher, one weight will be lower, it doesn’t matter.

But CPI, I can tell you, I did a study with this at Bancreek. I can predict almost exactly, with like 99% certainty, when the AAA retail gasoline price gets finalized at the end of every month, which if you have a Bloomberg license, you have access to AAA data. If you don’t, it’s very hard to actually find that series.

It should be in the public domain, but it’s tough to get. So if you have that, average the entire month, compare it versus the past month, or compare those retail gasoline prices versus the last year, and then the gasoline component of CPI will come in almost spot on on that every single month.

That’s all they use. And so I’ve done the correlation. It’s like a .99 R, or .99 R squared. That’s just what it is. So I can tell you the gasoline component, we know that. So I mean, honestly, it’s July 10th right now, so we know exactly what the gasoline component is gonna be. I haven’t looked at it yet.

I should’ve gone, going into this podcast. But maybe I’ll send it to you and you can kinda post it in the show notes. We know exactly what that’s going to be going into next week’s CPI release. Everything else is just based on the methodology and the surveys and the error and the models and everything in the BLS.

And so I couldn’t tell you that like laundry services or gardening services were gonna be spiking, but yet they are. Like, I mean, I think—

Matt: But that means that this is the moving data point that basically drags—it doesn’t drag the others with it, but if something is the most volatile component and it’s this, then this is where you wanna understand where that surprise risk comes from in the whole data series.

Eric: Well, and I can tell you that that’s not the part. So gasoline is, you know, that individually is the single largest mover because it’s so volatile, and it’s a large weight.

But diesel is more important because that feeds into almost all the other ones. So think about gardening and lawn care services. Diesel. Think about, you know, all of your grocery store food. Diesel. Why is that the case? I mean, I also happen to work at a railroad, and so fuel surcharge is a really big thing for the trucking industry.

All runs on diesel. For the railroad industry, all runs on diesel. The fuel surcharge gets passed through to the consumers. Now, I’m not an expert on this, but I’m sure people are on this call. I find it very interesting that you’re hearing the Targets and the Walmarts of the world talking about reducing their prices in the face of clearly what could be dramatically rising costs for them because of, like, they’re having to eat fuel surcharge as it, you know, migrates through.

And this only gets worse and worse and worse if we have this on-again, off-again thing, and if the diesel inventories keep dropping. I mean, you saw, like, on the day where, this is telling. On the day where, like, we went back to war last week, and everyone started bombing again, that same day, the EIA inventories were released, and crude oil, commercial crude oil inventories actually went up because the refinery utilization dropped down.

But gasoline dropped by, like, two million barrels, and diesel dropped by, like, three million barrels. Diesel prices were up 13% that day. Like, this is the main choke point. People are most worried about diesel right now, and that’s very, very unsettling for CPI because that could be, like, permanent long-ter—not permanent, but it could be long-term inflation that works itself into CPI because all that kinda stuff has to get kinda passed through over time.

Unless Walmart and Target and Costco and all of them are willing to basically step in front of this bus or this train, pun intended, and say—

Matt: Buses and trains.

Eric: “We’re willing to kill our margins to basically protect the consumer,” which to me, if they’re willing to do that, that means not, like, the top 1%. They’re immune largely until the shit really hits the fan. But that means the rest of us are really, really suffering. ‘Cause, I mean, why would you, as, you know, someone that cared about quarterly reports, as one of these large retailers, you’re looking at rising costs pretty obviously as fuel surcharge passes through.

Why would you ever cut costs right now unless you were really, really, really concerned about volume? At the low-cost retailers. So that’s a concerning data point. Don’t take my word for it because I don’t read these transcripts. I just saw, you know, news in passing. So go out, validate that for yourself.

If they really are cutting that, that is something that I would really wanna understand. But my own, like, I shop at Walmart every week. Again, we’re a nonprofit, so I have to shop at Walmart. And I can tell, like they are cutting prices, like at least in my... Like anecdotally, I’m shocked.

I’m really shocked that they’re doing it given the inflationary pressures that they’re probably just subsidizing at this point in time. It’s interesting. Really, really interesting what’s going on.

Matt: It’s fascinating, especially when we get into corporate earnings or we get into this, and this is a broader question that keeps coming up on Excess Returns, is this idea of how corporations are thinking of it.

If you’re spending on CapEx and AI and other places, you’re cutting somewhere else. Different companies are reallocating right now. I wanna land us here because this is now the combination of all this data, at least in my mind, and this is with financial planning hat on, this is when I go through yet another review of taxes and spending and budgeting in an exercise, and we go, “Here’s another person whose grocery and basic income expenses, whatever, it didn’t go up 3% or 5% this year.”

It went up 50% or 60%.

Seeing it across the board, luckily a lot of the people we care about are at the upper arm of the K, not the lower leg of the K. Part of why bridging this makes so much sense. I wanna talk about the single income stress test. The precarity line. Shout out Adam Butler, Mike Green, the people who have done work on this, you as well.

Let’s talk about the single income stress test because I think if this economy is running on consumption, this is why this data is so important in understanding what the knock-on effects to everything else are.

Eric: Yeah. And this also goes back to the home healthcare thing. You know, it’s...

What I was really interested in, I took that same OEWS database, and this is one of the first visualizations I put together and published on Data For The People, is I was really interested in connecting the median wage for one worker. So we’re not talk—Like now, there’s other data in the visualization we first started talking about where you can look at people that have two jobs, and that’s at an all-time high, which this visualization you just asked me about will explain why.

So if you want to just work one job, like this to me is where like this whole like America’s greatness kind of went sideways and how it was kind of like weaponized. Like I think back to like the unions and like, I wasn’t alive during this period of time, but like—My understanding of this period of time was like you could actually have a middle class to upper middle class lifestyle, buy your own home, put your kids through college on one income.

And it didn’t have to be like I’m the president of an investment bank income. It could be like, you know, I’m like a senior person working at a factory, and I can do that. You know, that is a great thing if you can do that. It’s great. I mean, like look maybe your wife or maybe it’s the wife that works and the...

But I mean, I can tell you I’ve been in the situation where like my wife only worked when I was not bringing income when I’m starting Data For The People, and my kids benefit a lot from that. Like having a parent home, having a parent present for them to take care of them rather than just putting them in daycare like, you know, putting them in front of a tablet.

Like there are real, call it, you know, qualitative benefits that you get from that. So I look back and I’m like, all right, well, what if you wanted to do that now? What if you wanted to earn a median income in the city in which you live, Dayton, Ohio, let’s say, or I don’t know, say Philadelphia’s close to you.

I don’t know. So you wanna—

Matt: It’s an upgrade.

Eric: You wanna, yeah, you wanna own or you wanna earn a single income, how far above the poverty line to raise a family of four are you? It’s a model, right? Again, all models are wrong. Some are useful. I find this one really useful because it’s simulation. It’s not saying this is the number of people because most families have two earners now, right?

But what if you didn’t want that? Like you wanted those old days of where you could do... So the answer if you actually look through all of them, one, it shows you the gradient. So the more green you are, the higher above the poverty line you are. And then I also give you a little kind of, it’s called the parameter entry box.

So you can actually say, “Whoops, I have $5,000 of surprise expense. Whoops, I have $10,000. I had a healthcare bill. I had this.” Like you could just plug that in and say, “Well, take the poverty line and add that amount of money to it. Now how far above?” So like how much breathing room do I have? And what you find is if you put $15,000 in there, the whole country turns red.

So it doesn’t matter where you live, the whole country, the median income in those cities using the 2024 data, which is what I was using at that time, they only have $15,000 of breathing room, and that’s pre-tax too, so it’s probably even less than that, before they are living under the poverty line to support a family of four.

And so that’s why they have to work two jobs. We can start understanding more about the lived experience of people in the median. Now, go and switch that from median to 25th percentile or even to 10th percentile, everything is blood red. I mean, to actually... Like this is the thing that’s beautiful about Data For The People is like when I did that, I mean, I felt it.

Like when I switched it and I’m like, wait a second, 10% of all the people, 10%, this isn’t like a small percentage, of all the people living in the city make under like $16,000 a year, 17,000, 20,000. It’s just like a hole in my heart almost that it’s like, well, what if that were me? Like, I mean, I can’t even envision...

Like, I mean, like my wife that works a good government job, and like we really were struggling, like to kind of over the months of not having no income until I got this fellowship, gratefully to O’Shaughnessy Ventures. We were really, really, you know, budgeting aggressively and cutting back on things and just to make things meet on her very good salary.

And yet there are people that are making $20,000 a year, $30,000 a year. Like, I can’t even like fathom how that must feel, but I can start to. I can start to when I look at this data and I really try to get myself out of my own, you know, privilege problems and start to see through the lens of other people.

And that’s what I’m really... Look, there’s a lot of investing takeaways, so many, if you still believe that the economy has anything to do with the market. Big qualifier, big asterisk there. But I mean I think—

Matt: Take us here because I think this is a great place for us to put the bow on this conversation. The work with Data For The People, about to be officially a nonprofit. Congratulations on making that move.

Eric: Thank you.

Matt: Another reason to check out the site, you can support work like this, because there are direct market implications of understanding these data sets, but I also know there’s a deep personal connection that you feel, I feel this too, where you think about your kids, you think about your kids’ kids, and you say, “This is not a sustainable framework to build the next several generations on because we’re not using the data that’s at our disposal.”

Eric: Yeah. Yeah.

Matt: Talk to me about the mission for the company going forward.

Eric: Yeah. So, yeah, thanks for the shout-out. We literally am just submitting the... Right now, simply because of cost, I was in an LLC structure with a DBA, doing business as for Data For The People. I now, you know, I’m filing for an Ohio nonprofit corporation.

I’m hoping that will be done next week. Transferring the name over or giving rights to use the name. And then, yeah, then we’ll be going through the Form 1023 process, you know, getting the 501(c)(3) status. And I will keep people updated on how that goes, because this is not a Substack model.

There is no paywall. There never will be a paywall on our work. I want everybody to have access to this, and I don’t wanna have to keep pestering you about, you know, paying money for this. I refuse to do that. But ultimately, our work will be supported by those that see value in it and can afford to do it.

Like, if you can afford $10 a month, it’s totally up to you. I don’t wanna know your financials, but, like, that goes a long way to us. You know, even if I had, like, 100 people that could afford $10 a month, I mean, it’s a meaningful amount of money for us. And I understand that it’s prohibitive right now because I’m not a 501(c)(3), but I will be.

So right now, if you look at the website, we’re publishing at a frenetic pace thanks to—

Matt: It’s a good word for it. Frenetic is an accurate description.

Eric: Thanks to the magic of AI. You know, I have figured out how to play nice with AI and how to use it to do things that I never could have envisioned doing.

Like, the data visualization that we talked about to start, impossible to do without AI. Not with my skill set. I’m not smart enough to do it. And that’s because when you actually go into the raw database that lives underneath the unemployment data, there are at least 30 different dimensions with intersections of every single dimension, and many of those are blank.

And so when I get the intersection of sex and age, that will be populated. But then if I try to intersect that again with another dimension, say race, oop, all of a sudden it’s blank. I spent days and days trying to wrap my head around it until, like, you know, my head was spinning, and I gave up. And so I focused a lot on nativity because I think there’s amazing stories about immigrants versus native-born.

Look at the data visualization. I’ve written about this at length. But that’s about all the scraping I was able to do on my own. And then, you know, we have all this wonderful access to Anthropic’s Fable for another couple weeks or another week, and I basically just went to Fable and I’m like, “Do this all for me.”

And it did. You know, and of course it takes tremendous amount of editorial oversight to make sure it’s doing it right and testing the code and everything, which fortunately I’m skilled to, and I know how to do this. But my gosh, the amount of crank turning that it did and the amount of, like, testing and connections and then even specifying that I only want you to present these dimensions when they’re available and, like, be smart enough to know to default to the age group of 16 plus when you’re looking at the combination of race and sex.

And it just figured it all out. So that kind of stuff has allowed me to take what would’ve taken me about two weeks and do it in two hours now. That’s why I’m able to publish every single day a new original data research study. Yesterday or this morning’s piece, like I actually for the first time went down into the census’s microdata.

Which if you’ve ever heard about that, don’t go anywhere near it unless you’re using AI because it is, you know, you’ll just be committed to a loony bin. Impossible to decipher what’s going on. But if you want the intersection of every single dimension, microdata, that’s where you get it.

And I was able to unearth some amazing findings that nobody had ever looked at, that America is far older than we thought. You know, there was a change in the way that the models were measuring the age of people, and we lost about two and a half million prime age workers. So that’s a big deal, you know?

It’s a big deal for Social Security, for all these things. I was able to figure that using AI. So long story short, like we’re doing a ton of data journalism right now, but I archive everything I do, every chat I have, and everything that we’re doing is being used to train an LLM on—And it’s not just me, there are other people that are doing this.

There’s Jonathan, there’s other data fellows. Like all of our interactions is being used to train a special purpose-built LLM to understand how to triage problem-solving within data storytelling and data analysis and data visualization. So how do you basically create a digital twin of us?

Then on the other side, shout out to Amanda Sinton, who is our founding data architect. She is brilliant, and she’s building the entire architecture for how do we rescue data sources, how do we publish them on GitHub in a way that everybody can use for free, and then how do we integrate that into an AI intake agent that anyone can go to.

And there are many reasons why AI, I call it the everything store AI, which is what all like Claude is and Gemini and everything. Many reasons why it can’t do this. But for people that, and I really think local journalists, community advocates, just interested people that have problems that they wanna solve, it could be investors too.

If you really want a research assistant that is trained on the art of working with data and helping you kind of problem solve on how to get to the scope of something that actually is achievable to solve, and then can it create charts and data visualizations in a story and all the narrative for then you to edit.

Like I don’t think this should be an AI only tool. There always needs to be the human editorial oversight because we are the source of creativity and storytelling, right? But I think we can get to doing 80% to 90% of the work for you with an AI bot. And so that is all being built out. So right now we have Amanda working on one side, building the infrastructure for this platform, and me feverishly creating as much content as I possibly can do, solving every question or answering every question that I’ve ever had by using AI in this responsible way, and then taking myself out of being the crank turner to being the, call it the idea generator.

I’m always generating the ideas. I’m almost always creating the stream of consciousness piece, the writing on it. Like, I do the data work with Claude, with AI. I’m like, “Here’s the story that I see.” And then I am spending the vast majority of my time in an editorial role. Oversight. Claude is really bad at—sometimes it wants to go too far with the claim, sometimes it doesn’t go far enough.

Like, sometimes it will make, like, one little statement that you’re like, “You’re gonna torpedo the entire credibility of the entire piece based on that statement.” So you have to be very careful on an editorial basis, which is the stuff that, like, I’m really learning, looking to build that into the LLM so it doesn’t go anywhere near that.

Which if you just go create something right now, it will do that. And so—

Matt: It’ll run into that wall real quick.

Eric: So that’s, yeah, so like we’re just learning. We’re learning a lot about what it’s really good at, and where it is good, oh my gosh, it is like universe-changing good. And then where it’s not, it can basically destroy all the work that it’s good at.

Like, so it’s like how do you build that infrastructure that takes the best of it and then really filters it so if, like, if you go and you ask a question that is, like, clearly profit-seeking, we’re gonna direct you to go to Gemini. Like, we’re not gonna... We’re, that’s not what we’re for. The problem ultimately, and I’m not saying it’s not for investors, but it’s for people that care about building as robust and as strong of an America as possible for all of us.

Investing can overlap with that. Sometimes it doesn’t. And so we’ll know how to ferret out the questions and which way you’re going with it. And then, you know, we’ll either choose to help you or we’ll be like, “You know what? This is not what our free service is for.” So that’s what we’re looking to build.

Matt: Eric, insightful as always. One more time, just tell the people where to find it. Tell them where they can bug you on the internet.

Eric: Yeah. So the best place to find me on my website, data4thepeople.com. Number four, not F-O-R. We’re moving up in all the search rankings, so you can just search for Data For The People.

We’ll come up. We should be, you know, number one on that list, so you can do that if you forget. Email me. It’s eric@data4thepeople.com. And sign up for the distribution list. I’d love to hear feedback. I’m getting a lot more engagement, especially from this crowd. I love it, you know, when people tell me good or bad, you know, be critical with what I’m writing.

I love that. I wanna get engaged on the debates that are coming out of this data. I put a lot of my own bias into my interpretation of what I’m seeing. I will not allow any of my bias into how the data is worked. All the methodology is free. You’re free to recreate your tools, and you’re free to come up with completely different conclusions than me.

I believe, I mean, our vision ultimately is to create a shared basis of reality for America and for the world, you know? And data can do that if we choose to use it for good, but that’s not to say that we can’t have polar opposite viewpoints. We are allowed to have that. That’s what makes America beautiful, but we can’t have our own sets of data.

We just can’t get by with that because then we actually can never see each other’s perspectives. So if we can be any part of building that foundation, and if you can be any part with supporting us, especially once we’re a 501(c)(3), just following our work, telling people about it, right? I’m not on social media that much, although we’re trying to automate the entire process to shove out a whole bunch of things.

So you’ll see more posts coming from Data For The People. But please, if you value our work, let people know. You know, spread the word. It’s all organic. It’s all word of mouth. I’m really relying on you to do that.

Matt: Spread the word, data4thepeople.com. Eric, thanks so much for joining me today.

Eric: Yeah. Thanks, Matt.

Matt: Excess Returns in all the places. You know what to do. Like, comment, subscribe. Send Eric an email. All the things below, and we’re out.