I offer a cleaned version of the state-level NSDUH in Stata .dta and Excel .xlsx formats here.
The NSDUH is mostly quite good as government datasets go- they share individual-level data in many formats and with the option to get most years together in a single file. But due to privacy concerns, the individual-level data doesn’t tell you what state people live in, which means it can’t be used to study things like state policy. SAMHSA does offer a state-level version of their data, but it is messy and only available in SAS format. So I offer the 1999-2019 state-level NSDUH Small Area Estimation Dataset in Stata .dta and Excel .xlsx formats here.
If you have Stata I recommend using that version, since the variables are labelled, making it much easier to understand what they represent.
This is the latest addition to my data page, where you can find cleaned/improved versions of other government datasets.
Remember that one time, back when we had a global pandemic, when interest rates fell really low and everyone was borrowing and refinancing? Good times. But they were also times of surging demand for durable goods, supply chain disruptions, and shortages. Specifically, the price of lumber surged by 54% between 2019 and 2022. There were stories of contractors who were unable to do their jobs at their typical prices. Some of them went without work. Others did much less work. Theft of precious lumber was in the news.
As we know, sudden price spikes often make the front pages and the social media rounds. But they peter out and the subsequent decline in prices hardly ever gets coverage in the same way. People used to talk about higher gasoline prices all the time, but never discussed with the same enthusiasm when prices fell. The same is true for lumber. We heard hysterical stories of record high prices, alleged shortages, and the sawmills that lacked adequate capacity to keep up with demand.
A new essay by J. Zachary Mazlish answers the title question in the affirmative: yes, inflation made the median voter poorer. The post is data-heavy, with lots of charts and different ways of slicing the data, which is great! But since I am called out by name (or rather, my evil twin, Jeremy Horpendahl), I want to respond specifically to the claim about my data, but also I’ll make a few broader points.
Regular readers will recognize the chart in that Tweet comes from an EWED post from April 2024. Mazlich says that my chart and others like it are “misleading for understanding the election because a) they compare wages now versus January 2020, rather than January 2021.”
Fair enough, but if you read my Tweet you will see that I am specifically responding to an NPR story which said, “if you look at the difference between what… groceries cost in 2019 and what it costs today, and what wages looked like in 2019 and today, the gap is really gigantic.” So, they are specifically using 2019 as a baseline in that story, and my chart specifically used that as the baseline too! That’s why I thought that chart was relevant.
It’s true, of course, that if you want to understand median voter sentiment about the Biden administration, you should probably start the data at the beginning of the Biden administration. But I was responding to the more general claim people make, that they are worse off than in 2019.
With that clarification out of the way, what does Mazlich’s broader post say?
If you’ve ever been vegetarian or if you have ever spoken to a vegetarian about their diet, then you have probably heard or asked “How do you get enough protein?”. While it’s important for health and economic achievement to get adequate protein, not too long after comes the questions about types and sources of protein. This question is relevant for vegetarians and vegans, but also people with meat allergies and people with religious dietary guidelines that prohibit meat always or seasonally. Let’s break it down.
Some omnivores are incredulous that vegetarianism can provide adequate protein or protein quality. But protein itself is relatively easy to get and any judgmental attitudes on both sides are mostly just vibes. Legumes and nuts tend to have a lot of protein. But relative to what?
The World Health Organization recommends that an 80-kilogram (176 lb) adult should get 66.4 grams of protein per day (0.83g per kg). That’s the protein content of about a 9oz of peanuts. Protein is super important and it’s luckily not that hard to get if you eat a variety of foods. Even if you’re trying to consume double the WHO recommended daily intake (RDI), it’s an easy feat.
Below is a table of some popular protein sources. The table includes the grams of protein per 100 grams of food, which makes the protein content a percent. The table also includes the number of grams needed in order to achieve the WHO protein RDI of 66.4 grams. The last column is for our American readers who need the serving to be in ounces.
Last week I laid out my own expectations for what economic policy would look like in a Trump or Harris presidency. Now after yesterday’s market reaction, we can infer what market participants as a whole expect by roughly doubling the size of yesterday’s market moves. Prediction markets had a 50-60% change of Trump winning as of Tuesday morning’s market close, which moved to a 99+% chance by Wednesday morning. Look at how other markets moved over the same time, multiply it by 2-2.5x, and you get the expected effect of a Trump presidency relative to a Harris presidency. So what do we see?
Stocks Up Overall: S&P 500 up 2%, Dow up 3%, Russell 2000 (small caps) up 6%. My guess this is mostly about avoiding tax increases- the odds that most of the Tax Cuts and Jobs Act gets renewed when it expires in 2025 just went way up. Lower corporate taxes boost corporate earnings directly, while lower taxes on households mean that they have more money to spend on their stocks and their products. Lower regulation and looser antitrust rules are also likely to boost corporate earnings.
Bond Prices Down (Yields Up): 10yr Treasury yields rose from 4.29% to 4.4%. This is the flip side of the tax cuts- they need to be paid for, and markets expect they will be paid for through deficits rather than cutting spending. The government will issue more bonds to borrow the money, lowering the value of existing bonds.
Dollar Up: The US dollar is up 2% against a basket of foreign currencies. I think this is mostly about the expected tariffs. People like the sound of the phrase “strong dollar” but it isn’t necessarily a good thing; it makes it cheaper to vacation abroad, but makes it harder to export, even before we consider potential retaliatory tariffs.
Crypto Way Up: Bitcoin went up 7% overnight, Ethereum is now 15% up since Tuesday. Crypto exchange Coinbase was up 31%. Markets anticipate friendlier regulation of crypto, along with a potential ‘strategic Bitcoin reserve’.
Single Stock Moves: Private prison stocks are up 30%+. Tesla is up 15%, mostly due to Elon Musk’s ties to Trump, but also due to tariffs. Foreign car companies were way down on the expectation of tariffs- Mercedes-Benz down 8%, BMW down 10%, Honda down 8%.
Sector Moves: Steel stocks are up on the expectation of tariffs, while solar stocks (which can’t catch a break, doing poorly under Biden despite big subsidies and big revenue increases) were down 12% in the expectation of falling subsidies. Bank stocks did especially well, with one bank ETF up 12%. This gives us one hint on what to me is now the biggest question about the second Trump administration- who will staff it? I could see Trump appointing free-market types, or wall-streeters in the mold of Steve Mnuchin, or dirigiste nationalist conservatives in the JD Vance / Heritage Foundation mold, or an eclectic mix of political backers like Elon Musk and RFK Jr, or a combination of all of the above. The fact that bank stocks are way up tells me that markets expect the free-marketers and/or the Wall-Street types to mostly win out.
Just Ask Prediction Markets: If you want to know what markets expect from a Presidency, you can do what I just did, look at moves the big traditional markets like stocks and bonds and try to guess what is driving them. But increasingly you can skip this step and just ask prediction markets directly- the same markets that just had a very goodelection night. Kalshi now has markets on both who Trump will nominate to cabinet posts, as well as the fate of specific policies like ‘no tax on tips‘
Last night was a big win for Trump, but it was also a big win for prediction markets. In January 2024, I suggested that one of the best ways to follow the election was by following prediction markets. That prediction turned out to be correct!
Before any polls had closed, prediction markets had Trump with about 60% odds of winning. That’s far from a sure thing, but it’s much better than many prediction models, which all had the race as basically a 50-50 toss-up with a very slight edge to Harris (though one simple model that I wrote about two weeks ago had Harris slightly losing the popular vote, a good call in hindsight). So going into the election results, you would have been more confident that a Trump win was a real possibility if you watched predictions markets
Last night after the results started coming in, the average over five different prediction markets from Election Betting Odds put Trump at over 90% odds by 11:00pm Eastern Time. By about 12:45am, he was already over 95%. These aren’t absolutely certain odds, but if you were watching the election night news coverage, they were still treating this as essentially a toss-up in the battleground states.
The Associated Press hadn’t even called Georgia, the second of the battleground states, by the time prediction markets were over 95% for the overall race! Decision Desk HQ, which is a very good source for calling races in real time, didn’t declare Trump the winner until 1:21am, when they called Pennsylvania (they also have a nice explanation of how they made the call). The AP didn’t declare Trump the winner until 5:34am, when they called Wisconsin.
Polymarket is the largest of the five markets in the Election Betting Odds average, and they are also a good source because they have markets for all of the battleground states (here’s the market for Michigan, which still hasn’t been called as of 11:30am on Wednesday by most news sources!). This table shows when the 90% and 95% thresholds were permanently crossed on Polymarket odds for each of the 5 early battleground states, in comparison with the DDHQ and the AP.
Notice that the 90% threshold consistently beats DDHQ by at least an hour (the one exception is North Carolina, where DDHQ called it very early — they are very good at what they do!). And the 90% threshold is consistently beating the AP by at least 3 hours.
None of this should be read as a criticism of the Associated Press. They should be cautious about predictions! But if you want to know things fast (or, before your bedtime in this case), prediction markets are clearly worth following.
How can prediction markets be so far ahead of media sources? Because there is a strong incentive to be right early: that’s how you make money in these markets! How exactly this is done is unclear, since the traders are all anonymous and we generally can’t ask them. But likely they are doing a similar analysis of counties results compared to the 2020 election, as DDHQ told us they did after the fact, just quicker (indeed, if you were watching news coverage, they were doing the same thing, just in an ad hoc way, and much more slowly).
In Fiscal Year 2019, the US federal government spent $4.45 trillion dollars. In Fiscal Year 2024, spending was $6.75 trillion, or an increase of $2.3 trillion dollars. If you adjusted the 2019 number for inflation with the CPI, it would only be about $1 trillion more. Where did that additional $2.3 trillion go?
It will probably not surprise you that most of the increase in spending went to the largest categories of spending. Historically these have been health, Social Security, and defense, but now we must also include interest spending (roughly equal in size to defense and Medicaid in 2024). Indeed, with these areas of spending, 72 percent of the increase is accounted for. Add in the next three functions, and we’ve already accounted for over 90 percent of the increase.
Importantly, most of these categories are outside of the annual federal budget process, meaning that Congress does not need to approve new spending each year (Congress could change them, just as it could change any law, but it’s not part of the annual budgeting process). The “mandatory” categories, as they are called in federal law, are shaded red. I’ve striped with red and blue the health and income security functions, because some of this is subject to the annual budget process, but most of it is not. For example, Medicaid is not subject to the budget process (biggest part of the “health” function) and SNAP is not subject to the budget process (a big part of income security — it is set by the Farm Bill, usually on a five-year cycle).
So, when we talk about the $2 trillion increase since 2019, or the roughly $2 trillion cuts that would be needed to balance the budget, keep in mind that most of this is not subject to the annual budget process. It would require Congress to consider them specifically to enact cuts — though some big categories, such as Social Security, would be automatically cut under current law once their trust funds are exhausted (coming up on about a decade for the Social Security Old-Age Trust Fund).
The experimental economics world is currently still doing data collection in traditional physical labs with human subjects who show up in person. This is still the gold standard, but it is expensive per observation. Many researchers, including myself, also do projects with subjects that are recruited online because the cost per observation is much lower.
As I remember it, the first platform that got widely used was Mechanical Turk. Prior to 2022, the attitude toward MTurk changed. It became known in the behavioral research community that MTurk had too many bots and bad actors. MTurk had not been designed for researchers, so maybe it’s not surprising that it did not serve our purposes.
The Prolific platform has had a good reputation for a few years. You have to pay to use Prolific but the cost per observation is still much lower than what it costs to use a traditional physical laboratory or to pay Americans to show up for an appointment. Prolific is especially attractive if the experiment is short and does not require a long span of attention from human subjects.
If you want to know how many pigs were killed in the United States yesterday, the USDA has the answer. But if you want to know how many humans were killed in the US this month, the FBI is going to need a year or two to figure it out. The new Real Time Crime Index, though, can tell you much sooner, by putting together the faster local agency reports:
Trends currently look good, though murders still aren’t quite back to pre-2020 levels.
In addition to graphing top-line state and national trends, the Real Time Crime Index also offers the option to download a CSV with city-level data going back to 2018. This seems like a great resource for researchers, worthy of adding to my page of most-improved datasets.
I don’t like to follow politics, much less politics in another country. Policy on the other hand? I’m always hooked.
Most of us have heard of President Javier Milei by now. He became Argentina’s president in December of 2023. Prior, he had been in charge of a private pension company, a university professor who taught macroeconomics, had hosted a radio show, and has written several books. See his Wikipedia entry for more.
What makes him worth talking about is that he appears a little… unique. He’s boisterous and rattles off economic stories and principles like he wants you to get up and do something about it. To anyone in the US, he looks and behaves like a weird 3rd-party candidate – sideburns and all. He’s different. Here he is bombastically identifying which government departments he would eliminate:
I’ve enjoyed the spectacle, but haven’t paid super close attention. I know that he is libertarian in political outlook, drops references to Austrian economists and their ideas by the handful, and doesn’t mince words. Here he is talking at the Davos World Forum (English & Dubbed).
So what?
Argentina has a long history of high inflation and debt defaults. Every president always says that they’ll fix it, and then they don’t. There have been periods of lower inflation, but they don’t persist. Among Milei’s stated goals was to end that cycle and bring down inflation. His plan was to substantially reign in deficit spending by eliminating entire areas of government. We’re now approaching a year since Milei took office, and I thought that I would check in. Below is the CPI for Argentina since 2018. As soon as Milei took office prices spiked, but have started coming down more recently. Similarly, the Argentine Peso has fallen in value by 50% since he’s taken office. Ouch!
Economist Writing Every Day 