Author: James Bailey

The Best Personal Finance Books

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Last week Scott offered a very negative review of one popular personal finance book, Rich Dad Poor Dad. My own take on the book is less negative, but I still wouldn’t recommend it to most people. That still leaves the question of which personal finance books are worthwhile. I gave my answer back in 2020 in a post on my personal blog. You can read the full reviews there, but I’ll give my short answers here:

I Will Teach You to Be Rich

Despite the title, the book is really about the basics of how to get out of debt, save for retirement, and manage credit. The material is stuff most people will figure out on their own by their 30’s or 40’s, but it’s a nice presentation all in one place and can save people from learning lessons the hard way. Perfect for a college student, someone at their first real job, or someone older who feels like they missed the memo on how all this works. His big idea is that once you set and meet good savings goals, you don’t need to feel guilty about the things you do spend money on.

The Millionaire Next Door

This book is built around surveying millionaires and finding the commonalities in what they did to get wealthy. The core idea is that Americans with millions saved tend to have moderately high incomes but very high savings rates. Even someone with a normal income can become a millionaire- income is different from wealth. The key is to live frugally and let the compound returns on your savings work for you. The original version of the book is inspiring, but has out of date numbers; the author’s daughter recently updated it (The Next Millionaire Next Door) with more current numbers.

There are many more books about how to invest, but for broad takes on personal finance overall these are the best two I have found, and the ones I recommend to students. Still interested to hear your thoughts on more recommendations.

Go East, Young Man

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Americans have moved westward in every decade of our history. But after over 200 years, that trend may finally be ending.

A new report from Bank of America notes that the share of Americans who live in the West has been falling since 2020:

The absolute population of the West is still growing slightly, but the Southeast is growing so quickly that it makes every other region of the country a smaller share by comparison:

I think this has a lot to do with the decline in housing affordability that Jeremy discussed yesterday. Americans always went West for free land, or cheap land, or cheap housing. Or in more recent decades on the Pacific coast, they went for nice weather and good jobs with non-insane housing prices. But now all that is gone, and if anything housing prices are pushing people East.

I see some green shoots of zoning reform with the potential to lower housing costs in the West. But I worry that this is too little too late, and that 2030 will confirm that our long national trek Westward has finally been defeated by our own poor housing policy.

Medicaid Cuts Mean Credit Card Debt

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My paper “Missouri’s Medicaid Contraction and Consumer Financial Outcomes” is now out at the American Journal of Health Economics. It is coauthored by Nate Blascak and Slava Mikhed, researchers at the Federal Reserve Bank of Philadelphia. They noticed that Missouri had done a cut in 2005 that removed about 100,000 people from Medicaid and reduced covered services for the remaining enrollees. Economists have mostly studied Medicaid expansions, which have been more common than cuts; those studying Medicaid cuts have focused on Tennessee’s 2005 dis-enrollments, so we were interested to see if things went differently in Missouri.

In short, we find that after Medicaid is cut, people do more out-of-pocket spending on health care, leading to increases in both credit card borrowing and debt in third-party collections. Our back-of-the-envelope calculations suggest that debt in collections increased by $494 per Medicaid-eligible Missourian, which is actually smaller than has been estimated for the Tennessee cut, and smaller than most estimates of the debt reduction following Medicaid expansions.

We bring some great data to bear on this; I used the restricted version of the Medical Expenditure Panel Survey to estimate what happened to health spending in Missouri compared to neighboring states, and my coauthors used Equifax data on credit outcomes that lets them compare even finer geographies:

The paper is a clear case of modern econometrics at work, in that it is almost painfully thorough. Counting the appendix, the version currently up at AJHE shows 130 pages with 29 tables and 11 figures (many of which are actually made up of 6 sub-figures each). We put a lot of thought into questioning the assumptions behind our difference-in-difference estimation, and into figuring out how best to bootstrap our standard errors given the small number of clusters. Sometimes this feels like overkill but hopefully it means the final results are really solid.

For those who want to read more and can’t access the journal version, an earlier ungated version is here.

Disclaimer: The results and conclusions in this paper are those of the authors and do not indicate concurrence by the Agency for Healthcare Research and Quality or the US Department of Health and Human Services. The views expressed in this paper are solely those of the authors and do not necessarily reflect the views of the Federal Reserve Bank of Philadelphia or the Federal Reserve System. Any errors or omissions are the responsibility of the authors.

Historical State GDP Data

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Data on Gross State Product prior to 2017 has disappeared from the main page of the Bureau of Economic Analysis. It is also gone from some third party hosts like FRED. It turns out BEA is in the middle of revising how they calculate state GDP; they have the new version done back to 2017, and took down the older inconsistent estimates until they can recalculate them. After that, they tell me they will repost pre-2017 state Gross Domestic Product:

In the mean time, they offer some messy and seemingly incomplete versions of pre-2017 GDP here, and you can find 1980-2021 state GDP (along with many other nice variables) in a nice panel from the University of Kentucky Center for Poverty Research’s National Welfare Data.

You can find more details on the actual changes BEA is making to how they calculate GDP here. Most changes seem relatively minor for states, but might have more impact on the measured relative size of industries. For instance, “equity REITs will be reclassified from the funds, trusts, and other financial vehicles industry to the real estate industry, while mortgage REITs will remain classified as funds, trusts, and other financial vehicles”.

Does More Health Spending Buy Better Outcomes for States?

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When you look across countries, it appears that the first $1000 per person per year spent on health buys a lot; spending beyond that buys a little, and eventually nothing. The US spends the most in the world on health care, but doesn’t appear to get much for it. A classic story of diminishing returns:

Source: https://twitter.com/MaxCRoser/status/810077744075866112/photo/1

This might tempt you to go full Robin Hanson and say the US should spend dramatically less on health care. But when you look at the same measures across US states, it seems like health care spending helps after all:

Source: My calculations from 2019 IHME Life Expectancy and 2019 KFF Health Spending Per Capita

Last week though, I showed how health spending across states looks a lot different if we measure it as a share of GDP instead of in dollars per capita. When measured this way, the correlation of health spending and life expectancy turns sharply negative:

Source: My calculations from 2019 IHME life expectancy, Gross State Product, and NHEA provider spending

Does this mean states should be drastically cutting health care spending? Not necessarily; as we saw before, states spending more dollars per person on health is associated with longer lives. States having a high share of health spending does seem to be bad, but this is more because it means the rest of their economy is too small, rather than health care being too big. Having a larger GDP per capita doesn’t just mean people are materially better off, it also predicts longer life expectancy:

Source: My calculations from 2019 IHME life expectancy and 2019 Gross State Product

As you can see, higher GDP per capita predicts longer lives even more strongly than higher health spending per capita. Here’s what happens when we put them into a horse race in the same regression:

The effect of health spending goes negative and insignificant, while GDP per capita remains positive and strongly significant. The coefficient looks small because it is measured in dollars, but what it means is that a $10,000 increase in GDP per capita in a state is associated with 1.13 years more life expectancy.

My guess is that the correlation of GDP and life expectancy across states is real but mostly not caused by GDP itself; rather, various 3rd factors cause both. I think the lack of effect of health spending across states is real, between diminishing returns to spending and the fact that health is mostly not about health care. Perhaps Robin Hanson is right after all to suggest cutting medicine in half.

Where is Health Care The Biggest Part of the Economy?

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State health care spending usually gets reported in terms of dollars per capita, leading to maps like this that show Alaska as the highest-spending state and Utah as the lowest:

Source: https://www.kff.org/other/state-indicator/health-spending-per-capita/

But states differ greatly in how rich they are and how much they have to spend. I wanted to know the states where health care takes up the largest and smallest share of the economy, so I got the data:

Health Care Spending as Share of State Gross Domestic Product in 2019:

Source: I divided 2019 National Health Expenditure Provider data on total health spending by 2019 Gross State Product data.

You can see that health spending as a share of GDP looks pretty different from health spending in raw dollars. We’ve gone from a high-spending North and low-spending South to more of a mix. Health spending is now highest in West Virginia, where it makes up more than a fourth of the economy; and lowest in Washington State and Washington D.C., where it makes up less than one ninth of the economy.

The biggest change when considering things this way is in Washington D.C., which has the highest spending in $ terms but the lowest as a share of GDP because it has an enormous GDP per capita. Many other states that spend a lot in $ also fall a lot in the rankings due to high GDP per capita, including Alaska, New York, and Massachusetts. The states that rise the most in this ranking are poor states like Arkansas, Alabama, and Mississippi. Mississippi rises the most, gaining 37 spots in the rankings of highest-spending states when we go from $ per capita to share of GDP.

I share the data here so you can do your own comparisons:

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Industries Without Investors

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Venture-capital backed startups almost all cluster in the same handful of industries, mostly various types of software. This leaves a variety of large and economically important sectors with almost no venture-capital backed startups. That means those industries see fewer new companies and new ideas; they must rely on either growth from existing firms, which are unlikely to embrace disruptive innovation, or on startups that bootstrap and/or finance with debt, which tend to grow slowly.

Venture capital firm Fifty Years has done a nice job cataloging exactly which industries see the most, and least, investment relative to their size. Here is their picture of the US economy by industry market size:

Now their picture of which industries get the investment (though unfortunately, they aren’t very clear about their data source for it):

They use this to create an “Opportunity Ratio”- current market size divided by current startup funding:

They call the industries with the largest Opportunity Ratios the “Top Underfunded Opportunities”:

I don’t necessarily agree; some industries face shrinking demand, prohibitive regulation, or other fundamental issues making them bad candidates for investment. Conversely, investors haven’t just focused on software randomly or through imitation; they see that it is where the growth is.

Still, herding by investors is real, and I always like the strategy of finding a new game instead of trying to win at the most competitive games, so I do think there is something to the idea of investing in an unsexy industry like paper. Growing up in Maine and watching one paper mill after another close, I always wondered how they managed to lose money in a state that is 90% trees, and whether anyone could find a way to reverse the trend. Perhaps related technology like mass timber or biochar will be the way to take advantage of cheap lumber.

Thanks again to Fifty Years for releasing the data.

ASSA 2024: Unrejected

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Is this the year the world’s largest economics conference settles into its new normal? ASSA 2024 starts in San Antonio today.

Like most conferences, the Allied Social Science Association took a big hit during the pandemic. Unlike most other conferences, a big fraction of this hit appears to be permanent. Part of what made ASSA so popular was that it was the site of most 1st-round job interviews for economists, but the pandemic made this shift to remote interviews. The American Economic Association decided the job market was better that way, so they made the arrangement permanent.

This shrunk their conference by about half compared to pre-2020; overall I thought it was still fine last year, but that the transition creates a problem:

The big problem with attendance falling to 6k is that they’ve planned years worth of meetings with the assumption of 12k+ attendance. Getting one year further from Covid and dropping mask and vaccine mandates might help some, but the core issue is that 1st-round job interviews have gone remote and aren’t coming back. The best solution I can think of is raising the acceptance rate for papers, which in recent history has been well under 20%.

I suspect the AEA is starting to take my advice. Acceptance rates ticked up slightly in 2023 (from 7% to 9% for individual papers, and from 16% to 30% for complete sessions). They have yet to release full information on acceptance rates this year, but my own experience indicates that this summer they realized they had a problem. I got a rejection email in July that said:

We were able to accept less than one third of the more than 1,150 submissions for paper or poster sessions.

This was followed by something I’ve never seen from an economics conference before- a rejection of the rejection:

You have probably already received an email saying your paper which you submitted for the American Economic Association program at the meeting in San Antonio, TX in January 2024 was not accepted. However, the AEA has decided to select a few more papers for the poster session.

I am pleased to inform you that your paper entitled

Certificate of Need and Self-Employment


which you submitted for the American Economic Association program, has been selected to be part of the AEA’s poster session.

This sums up my relationship to the core of the profession nicely: I’m exactly on the margin of it. But this time, just barely on the right side of it, helping them fill up a newly-oversized hotel block.

The odds aren’t what they were in the mega-conference days before 2020, but I expect I’ll still see some of you in San Antonio.

The Open Internet Is Dead; Long Live The Open Internet

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Information on the internet was born free, but now lives everywhere in walled gardens. Blogging sometimes feels like a throwback to an earlier era. So many newer platforms have eclipsed blogs in popularity, almost all of which are harder to search and discover. Facebook was walled off from the beginning, Twitter is becoming more so. Podcasts and video tend to be open in theory, but hard to search as most lack transcripts. Longer-form writing is increasingly hidden behind paywalls on news sites and Substack. People have complained for years that Google search is getting worse; there are many reasons for this, like a complacent company culture and the cat-and-mouse game with SEO companies, but one is this rising tide of content that is harder to search and link.

To me part of the value of blogging is precisely that it remains open in an increasingly closed world. Its influence relative to the rest of the internet has waned since its heydey in ~2009, but most of this is due to how the rest of the internet has grown explosively at the expense of the real world; in absolute terms the influence of blogging remains high, and perhaps rising.

The closing internet of late 2023 will not last forever. Like so much else, AI is transforming it, for better and worse. AI is making it cheap and easy to produce transcripts of podcasts and videos, making them more searchable. Because AI needs large amounts of text to train models, text becomes more valuable. Open blogs become more influential because they become part of the training data for AI; because of what we have written here, AI will think and sound a little bit more like us. I think this is great, but others have the opposite reaction. The New York Times is suing to exclude their data from training AIs, and to delete any models trained with it. Twitter is becoming more closed partly in an attempt to limit scraping by AIs.

So AI leads to human material being easier for search engines to index, and some harder; it also means there will be a flood of AI-produced material, mostly low-quality, clogging up search results. The perpetual challenge of search engines putting relevant, high-quality results first will become much harder, a challenge which AI will of course be set to solve. Search engines already have surprisingly big problems with not indexing writing at all; searching for a post on my old blog with exact quotes and not finding it made me realize Google was missing some posts there, and Bing and DuckDuckGo were missing all of them. While we’re waiting for AI to solve and/or worsen this problem, Gwern has a great page of tips on searching for hard-to-find documents and information, both the kind that is buried deep down in Google and the kind that is not there at all.

Robert Solow on Sustainability

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2023 continues to be a dangerous year for eminent economists. We have once again lost a Nobel laureate who was influential even by the standard of Nobelists, Robert Solow:

I’m sure you will soon see many tributes that discuss his namesake Solow Model (MR already has one), or discuss him as a person. I never got to meet him (just saw him give a talk) and the Solow Model is well known, so I thought I’d take this occasion to discuss one of his lesser-known papers- “Sustainability: An Economists Perspective“. What follows comes from my 2009 reaction to his paper:

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