Should a Universal Basic Income Be Adjusted for Local Prices?
Kind Of. Depends on the Aim.
I was recently cited in a discussion of proper conservative perspectives on welfare reform. It’s an interesting read, whether you agree or not. You can also read the same author’s related views on a “Universal Basic Income” here. In the Twitter discussion of UBI, we got chatting about whether or not a Universal Basic Income (or, frankly, any welfare program) should be adjusted for local prices.
Some people pretty adamantly think the answer is “No.”
I, however, think UBI probably should vary across localities. But perhaps in some un-intuitive ways. Let’s think through some arguments for this issue.
What Makes Income Basic?
UBI guarantees people a “basic income.” Crucially, that’s not a minimum income. For example, if I get a $12,000 UBI, but lose, say, $30,000 due to a loss-making business, my actual income is -$18,000. UBI absolutely does not guarantee me a minimum income, it guarantees me a specific cash flow.
But if UBI is not in fact a promise of a minimum income, then what is it? People treat it as if it’s a promise of a minimum income because they have in mind pretty simple revenue situations, but that view is foolish. You can’t on the one hand hope that UBI would free up low-level entrepreneurship and on the other ignore the extremely volatile income situations of business-owners.
UBI is not, then, about a minimum income but a basic income, an income that forms a base or basis. We can interpret this two ways: first, that it’s a base on which other income sources are stacked, or from which they’re subtracted. I’ll call this the “Base Accounting Model of Basic Income” or BAMBI. Or, maybe it means basic as in basic needs, as in, the income should provide for the most rudimentary human needs. This is the idea that motivates many leftist advocates of UBI, and is the basic idea underlying the view that UBI could/should replace welfare. I’ll call this the “Welfare Allowance Model of Basic Income,” or WAMBI.
I think most people have in mind both of these concepts, but WAMBI probably predominates. Every time someone talks about replacing welfare, or guaranteeing basic needs, or freeing up resources for entrepreneurship, they’re appealing to the WAMBI concept of UBI, not the BAMBI concept. If they talk about UBI in terms of wealth redistribution, or enabling people to arbitrage local prices, or develop investment capital, they’re implicitly referencing BAMBI, not WAMBI.
For BAMBI, a locally-unadjusted (that is, flat) UBI makes sense. We guarantee people a cash flow, their use of it is their choice, and if their local area is too expensive, well, move!
For WAMBI, a locally-adjusted UBI is almost a necessity. If you’re guaranteeing people a basic standard of living, then you can either say, “No, we only guarantee that contingent on you living in the cheapest place in America,” or you can adjust for local prices.
What Do Local Cost Adjustments Do?
Think about the incentives involved in basic income.
If I’m guaranteed $12,000 a year, and I either do not want to work, or do not believe it is likely that I will obtain employment, then I can maximize my real income by living in the cheapest possible areas. I will stick with known networks, inherited assets, low-risk ventures, etc. In other words, a fixed dollar UBI encourages recipients to live in cheap, rural areas where they have extensive social networks. Fixed-dollar UBIs encourage poor people to locate in areas of high poverty and low opportunity.
On the other hand, let’s say we full adjust for local costs, and we’ll pay whatever it takes to guarantee a certain real income. In this case, recipients are totally unconstrained by location. That’s a good thing, because they can just focus on where their life opportunities are greatest. But, on the other hand, this is overwhelmingly likely to lead to tons of people flocking to amenity-dense areas, getting the government to foot the bill, and sharply increasing demand in those places. Imagine that every time San Francisco’s costs rise, everyone in San Francisco automatically gets a few hundred extra bucks, paid for by taxes on the rest of the nation. This situation is no bueno. Cost-adjusted UBIs subsidize areas with damaging housing policies, actively feed into local cost-spirals, and are likely to cost the government extremely large amounts of money.
Luckily, we can game the system!
See, the problem for flat UBIs is entirely at the low-cost end of the spectrum: they encourage people to live in poverty. Meanwhile, the problem for adjusted UBIs is entirely at the high-cost end of the spectrum: they encourage people to live in exorbitantly-priced areas, and may drive prices even higher.
This convenient asymmetry of problems clearly directs us to the solution. We should cost-adjust along the bottom half of the cost spectrum, and not the top half. Here’s how this works.
Say we have a UBI of $1,000 per month as the basic figure. For every metro area with a local price level 105% of the national average or less, we adjust the monthly grant to their local price level. So if local prices are 80% of the national average, UBI drops to $800/mo. And if local prices are 105% of the national average, UBI is $1,050/mo. But if local prices are 120% of the national average (hello DC, NYC, SF, etc), UBI is still just $1,050/mo.
This results in a kinked real-income curve with respect to metro area prices. Here’s what it looks like:
As you can see, when nominal UBI rises with local costs, the real UBI value is steady. In any city where local costs are 105% of the national average or less, the UBI fits the WAMBI model: we guarantee a certain basic standard of living. But, if you choose to live in an expensive city, it switches to a BAMBI model, where you have to manage your money as you see fit, and we make no promise that this “base” income will cover all your “basic needs.” This model subsidizes movement out of poverty, but doesn’t subsidize the bad policy choices or unfortunate geography of high-cost cities.
Does Price Really Represent Opportunity?
There are two basic concepts for thinking about welfare. We can think of it as aimed primarily at eliminating poverty, or at alleviating poverty. We can think of welfare as a safety net, or as a safety trampoline. Personally, I’m pretty stridently in the eliminationist/trampoline camp, but I recognize the need for alleviationist/net type policies, especially in the short run.
This has practical applications. If the only goal is to alleviate the effects of poverty, then we may want poor people to stay in poor areas, where their dollar stretches furthest. But I dislike this approach because, as I’ve said, cheap areas are often cheap because they’re poor.
But the correlation isn’t perfect. We could incentivize migration towards economic opportunity directly, by conditioning UBI on local unemployment rates.
And here we get a stark difference in alleviationist/eliminationist views of welfare and poverty. For an alleviationist, you’d want to make UBI more generous where unemployment is high, in order to (1) provide stimulus via more aggregate demand and (2) provide greater support to a struggling group of people. But this has the perverse (and empirically well-demonstrated) effect of making long-term unemployment even longer, unemployment rates higher, and long-term labor scarring even more severe (sidenote: yes, I believe long-term labor scarring is a real and important thing. You may disagree if you like).
On the other hand, we could make UBI less generous in places of high unemployment. The idea here is that when an area’s economy is contracting, we really want people to expand their geographical frame of reference for employment. It’s not that we necessarily want people to leave, it’s just that we want to provide incentives to break them free of the vice-grip of geographic inertia.
This method may make large upticks in unemployment even more painful than they would otherwise be, and may cause local economies to respond with even more volatility. These are bad effects. They are also not extremely likely to be permanent effects if we are actively incentivizing people to move towards economic opportunity, as helping unemployed people get employed is likely to yield net positive benefits for the nation on the whole, and out-migrants are unlikely to wholly and permanently sever ties with their homes. The problem with “positive national net” for trade is that the losses flow to different people than the gains. But the losses from unemployment land on the unemployed, and the gains from boosted migration to jobs are mostly going to flow to the (formerly) unemployed, so the “benefits” are primarily borne by people who bore the initial “costs.” In the long run, those who bear legacy costs of chronically depressed/indebted areas will also bear larger costs, but I’m on record as cheering for municipal default/restructuring, so we know where I stand on that issue.
It should be noted though that the ratio of local-area unemployment to national unemployment is uber-volatile, far more than local prices. This unemployment factor, then, could easily lead to mind-bogglingly vast differences in UBI; you could get $300/mo UBIs in some cities, and $5,000/mo UBIs in others. That level of variety is likely to be (1) expensive, (2) way more than is optimal, (3) incentivize overwhelming tides of migrants chasing the high-UBIs.
Let’s threshold it then. I like 50%/200% as unemployment rate ratio thresholds. I also worry that these may be excessive and that there may be extreme outliers, so I’ll take the square root of the post-threshold ratio of local unemployment rate to the national unemployment rate. In the end, here’s what nominal and real UBI look like, for a range of unemployment rates in 2014:
So if you’re in a city with 2% unemployment in 2014, you get just over $1,400/mo. Meanwhile, in a city with over 12% unemployment, you get just over $700/mo. And by the way, there are 5 cities with unemployment rates over 12% as of 2014: Yuba City, CA; Ocean City, NJ; Merced, CA; Visalia-Porterville, CA; Yuma, AZ; and El Centro, CA. Those last 2 are over 20%.
You can also see why my square-root choice matters: without it, the UBI rate ranges from $500 to $2,000, an enormous differential. As it is the gap I allow is pretty big, but I’m not sure it should be possible to quadruple UBI by moving from high-unemployment El Centro to low-unemployment Ames, Iowa. Even doubling, as I have it, may be too extreme.
What About Economic Cycles?
Yes, what about economic cycles? It does seem a bit unfair to punish cities experiencing high unemployment with even worse UBI.
My preferred solution is to use rolling-average rates. You don’t just use the latest price and unemployment figures; you use the rolling average of, as I chose, the most recent 3 years of unemployment and price data. I also decided I’d use the most recent 3 years for which both datasets are available. That means that, in 2016, we’re making local UBIs based on the average price and unemployment levels of 2012–2014.
A sudden spike in unemployment wouldn’t show up for years. This partly damages the intention of the policy, as UBI won’t change immediately, forcing people to move. On the other hand, locals will know that a sharp, lasting increase in unemployment will eventually reduce their UBI checks. This gives them time to respond: save up money to move, or try and attract businesses, or apply for Federal grants, or change local policies, etc. Having a lag means that people will have a plausible forecast of the UBI rates for a local area years in advance. Federal agencies could even publish UBI forecasts. The expectational channel would be beneficial, as communities could expect future income shocks. Heck, employers could even have an idea of communities where there’s likely to be more unskilled labor coming online as lower UBI draws more people into the market.
Plus, using 3-year averages shields communities from sudden changes. The only areas that are really penalized are areas with enduring high prices or unemployment. We might not want to incentivize people to leave communities who just had a bad year. But when they have years and years of bad years, then we might want to encourage departure.
I used a 3-year average. You could prefer a 5-year. That’s fine.
So we have 6 datapoints for 2014: the 2012, 2013, and 2014 price-based UBIs, and the 2012, 2013, and 2014 unemployment-based UBIs. If we average all 6, we can derive a “price-and-unemployment-adjusted local UBI.”
The Best UBI Calculation (For Eliminationists)
This UBI calculation rewards people who live in areas with low unemployment and moderate costs. It penalizes people who live in areas with high unemployment and very low price levels (or very high price levels, in real terms).
Sadly, Datawrapper, my visualization provider, does not do either US metro-area maps or scatterplots. Super-lame. So I must commit a heinous crime against your eyes, and show you a screenshot of some wonky excel charts:
The above chart uses the actual data for all US metro areas (no non-metro areas are included, just because of data constraints and convenience).
At top left, you can see that UBI’s nominal value rises consistently (moves to the right) as price level rises from, say, 75 to 95 or so. But ultimately, the nominal relationship between price and UBI is fairly weak. There could be several reasons for this. First of all, the variation in UBI due to unemployment may still be too large: maybe instead of 700–1400 I should restrict it to 800–1200 or something. Or perhaps the price component ought to be more heavily-weighted.
Second, there may be (read: there is) an association between price and unemployment. When unemployment rises or falls significantly, local prices tend to respond inversely. Ergo, one reason the price graph is messy is because price is associated with our other UBI determinant, unemployment.
Which brings us to that determinant! There’s a pretty strong relationship between nominal UBI and the unemployment rate, as you can see in the top right. As unemployment falls, UBI rises.
Now we come to the real UBI. We can take each metro area’s nominal UBI, and adjust it for local price levels. As you can see, cheaper areas still have higher real UBI. But the relationship has changed relative to a flat-rate UBI. Consider: the correlation between local price levels and the real value of a flat-rate UBI is -97%. The correlation between local price levels and the real value of the locally-adjusted UBI is just -51%. Most of even that correlation is at the high end (the left side of the graph), where very pricey cities have very low real UBIs. By the time we get down to about a 100 price level (that is, to national average price levels), there’s almost no relationship between real UBI and local prices. In other words, under this system, there are strong incentives to leave or avoid high-cost cities, while incentives among low- or medium-cost cities depend almost entirely on the strength of local economies.
And that brings us to the last graph. As you can see, the strong negative relationship between unemployment rates and UBI continues, although it is not as strong, largely due to a cluster of high-cost cities out there on the left side of the graph.
For eliminationists like me, these are nice graphs to see. We’ve accomplished most of what we set out to do. People have big incentives to avoid really costly cities and no incentive to linger in cheap areas without jobs, while they have very strong incentives to move to work. Essentially, this system is the government stepping in and insuring people against employment and cost-based risk associated with labor migration. I’m on record many times saying that, if we’re going to have any kind of welfare, that’s probably the best kind of welfare, so obviously I like what I see here.
If you’re an alleviationist (and that’s really okay if you are; I’m not, but I get why you would be), these graphs are kinda scary. Your only consolations are semi-speculative hopes that (1) employment shocks will be temporary and data production will have a long lag and, (2) that unemployment and prices will be correlated, meaning that UBI losses do to higher unemployment can be offset by UBI gains due to lower prices. These are not overwhelmingly optimistic things to hope for. Then again, in the long run, you might very correctly believe that the increased opportunity, economic freedom, geographic (and economic! and social!) mobility, and overall economic efficiency will increase economic growth for everyone, with the biggest rewards likely going to people who migrate, who are likely to be the formerly unemployed. But that kind of long-run gain can be a tough sell to suffering people, for understandable reasons.
Are You High, Lyman? UBI Is a Joke.
Correct! UBI is a joke! Never gonna happen!
But all these rules apply just as easily to every welfare program. Federally-supported affordable housing is semi-equivalent to cost-adjusted benefits; but it usually focuses on lowering costs in expensive cities, the opposite of what I suggest is important. We shouldn’t be working overtime to let people stay in costly places, we should be working to let people move from concentrated poverty into opportunity. Displacement is not as large a problem as involuntary or quasi-voluntary immobility.
We could apply this logic equally well to TANF, or SNAP, or Disability insurance, or Unemployment Insurance, or any of the gazillion programs provided by the Federal government. Each of them has its own set of rules. Strictly in-kind benefits tend to be sort of like de facto local-price-adjusted benefits. Cash- or cash-like benefits tend to be de facto flat-rate benefits. Our current mix of these methods is haphazard, and its net effect is broadly to encourage poor people to cluster in poor places. This is, by and large, not a good thing.
And to be clear, if welfare money was going to meaningfully stimulate an economy, I can’t help but think Eastern Kentucky would be a tiny bit richer than it is now. If anyone tries to tell you that TANF is going to be a big component of local aggregate demand or a basis for serious economic growth, it’s appropriate to begin giggling to yourself, not least because TANF rules in 42 states and the District of Columbia prohibit recipients from permanently escaping poverty (that is, from accumulating assets). Welfare programs do many valuable things, but propel lasting economic prosperity they do not.
So Your Point Is…
UBI serves as a very nice reduced-form way to think about how welfare rules, and especially programmatic relationships to local costs and economic outcomes, can impact behavior. Admittedly, no UBI is ever going to become law because it’s a bunch of namby-pampy commie codswallop, but its fun to use these hypothetical arguments to explore different policy options. Permitting UI bonuses to facilitate migration is a real policy option; so is regionally-adjusting the benefits from cash- or cash-like benefits programs; so are regional adjustments to minimum wage. With the UBI clarifying model in our head, we can think about different ways to approach and consider these more plausible policy options.
Check out my Podcast about the history of American migration.
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I’m a graduate of the George Washington University’s Elliott School with an MA in International Trade and Investment Policy, and an economist at USDA’s Foreign Agricultural Service. I like to learn about migration, the cotton industry, airplanes, trade policy, space, Africa, and faith. I’m married to a kickass Kentucky woman named Ruth.
My posts are not endorsed by and do not in any way represent the opinions of the United States government or any branch, department, agency, or division of it. My writing represents exclusively my own opinions. I did not receive any financial support or remuneration from any party for this research. More’s the pity.
