Data

How to Get People Vaccinated for 93 Cents

Jeremy HorpedahlLeave a comment

We’ve talked a lot about vaccines on this blog, including both the benefits of vaccines and how to get people vaccinated. For example, last month I posted about Robert Barro’s estimate on the number of additional vaccines needed to save 1 life. Barro put it at about 250 vaccines. Using some reasonable assumptions, I further suggested that each person vaccinated has a social value of about $20,000. That’s a lot!

But how do we convince people to get vaccinated? Lotteries? Pay them? In addition to just paying them (the economist’s preferred method), another good old capitalist method is advertising (the marketer’s preferred method). And a new working paper tries just that, running pro-vaccine ads on YouTube with a very specific spokesman: Donald Trump.

Running ads on YouTube is pretty cheap. For $100,000, the researchers were able to reach 6 million unique users. And because they randomized who saw the ads across counties, they are able to make a strong claim that any increase in vaccinations was caused by the ads. They argue that this ad campaign led to about 104,000 more people getting vaccinated, or less than $1 per person (the actual budget was $96,000, which is how they get 93 cents per vaccine — other specifications suggest 99 cents or $1.01, but all of their estimates are around a buck).

Considering, again, my rough estimate that each additional vaccinated person is worth $20,000 to society (in terms of lives saved), this is a massive return on investment. Of course, we know that everything runs into diminishing returns at some point (they also targeted areas that lagged in vaccine uptake). Would spending $1,000,000 on YouTube ads featuring Trump lead to 1 million additional people getting vaccinated? Probably not quite. But it might lead to a half million. And a half million more vaccinated people could potentially save 2,000 lives (using Barro’s estimate).

I dare you to find a cheaper way to save 2,000 lives.

John List, Dramatist

Joy BuchananLeave a comment

As someone who has dabbled in lab experiments for over a decade, I’m familiar with complaints about external validity. If an experiment is run with only college students, then how can we know if the finding will generalize to other populations? It’s a question worth asking, but many questions are worth asking and it doesn’t mean that controlled experimentation can’t add value to the economics literature. In the age of general suspicion of small studies, people say that replications are needed. We should only trust a conclusion that is supported by multiple studies. The thing about replications is that the process has to start somewhere. Empirical work has to get read and published. Replications are composed of individual studies.

I just met John List at the Alabama stop on his epic national book tour. He directed me to his work of art: Ungated Link. He wrote a play in response to the attacks on his work concerning external validity. He employs a rhetorical strategy of making your critics look obtuse. Even though the play is absolutely silly (thoroughly entertaining), he builds a strong defense for doing experiments. It is literally presented as the arguments of a defense lawyer. Before the trial begins, a “reporter” summarizes the conflict that has created the need for a formal trial:

Court Reporter Clifton Hillegass: Thank you Judge Learner. While it is never easy to convey succinctly the key points of a debate, this dispute has crystallized in a manner that leaves no middle ground. The prosecution, led by Mr. Naiv Ete, argues that all empirical work in economics must pass a set of necessary external validity conditions before being published in academic journals or used by policymakers. To date, in this courtroom no empirical work has passed his conditions, effectively rendering the question of generalizability beyond dispute, or as Livius Andronicus reminded us, Non est Disputandum de Generalizability. Ms. Minerva, Lead Defense, has argued that this line of reasoning leaves only theoretical exercises and thought experiments to advance science and guide policymaking, an approach that she fears will return us to the dark ages.

The paper is called “NON EST DISPUTANDUM DE GENERALIZABILITY?” It’s a good refresher on the history of science, not just economics.

Maybe the first best is for you to spend your weekend reading dense technical papers. But if you aren’t feeling up to that, then this play will make you feel like you learned something without even trying.

I’ll link this up to some of the posts I wrote last year about experiments and critics:

Calling Behavioral Economics a Fad

Behavioral Economist at Work

Dressed for Recess(ion)

Zachary Bartsch1 Comment

In my previous post, I decomposed consumer expenditures to figure out which service sectors experienced the largest supply-side disruptions due to Covid-19. I illustrated that transportation & recreation services were the only consumer service to experience substantial and persistent supply shocks. Health, food, and accommodation services also experienced supply shocks, but quickly rebounded. Housing, utility, and financial services experienced no supply disruptions whatsoever.

What about non-durables?

Total consumption spending is the largest category of spending in our economy and is composed of services, durable goods, and non-durables. Services are the largest portion and durable goods compose the smallest portion. So, while there were plenty of stories during the Covid-19 pandemic about months-long delivery times for durables, they did not constitute the typical experience for most consumption.

Even though it’s not the largest category, many people think of non-durables when they think of consumption. Below is the break-down of non-durable spending in 2019. The largest singular category of non-durable spending was for food and beverages, followed by pharmaceuticals & medical products, clothing & shoes, and gasoline and other energy goods. Clearly, the larger the proportion that each of these items composes of an individual household budget, the more significant the welfare implications of price changes.

Continue reading →

The Fed is Still Under-Reacting to Inflation

James Bailey6 Comments

In March the Federal Reserve raised rates for the first time since Covid began:

They also began to shrink their balance sheet:

Hard to see but its already down $25 billion from a peak of $8.962 trillion

These moves are in the right direction, but represent a slow start to tackling inflation that is the highest of my lifetime, with the CPI up 8.5% over the last year. While temporary supply constraints are contributing to this, it seems clear to me that excessive aggregate demand is a major driver of this inflation. The labor market has already recovered, with unemployment at 3.6% like it was in late 2019. The Covid-induced output gap is fully eliminated by one standard measure:

But market-based measures of inflation expectations remain high. The TIPS spread predicts that inflation rates over the next 10 years will be much closer to 3% than to the Fed’s target of 2%:

My preferred measure, the NGDP gap, is at 3% (i.e., 3% over the ideal level of 0)

Source: https://www.mercatus.org/publications/monetary-policy/measuring-monetary-policy-ngdp-gap

Overall, its seams clear that Fed policy is currently too loose. The harder question is, what exactly to do about it? How much should they raise rates? The simplest way to answer this is to use the Taylor Rule. Using the version of the rule that Bernanke describes here and using core PCE as the inflation measure (currently just 5.4% yoy, vs 8.5% for headline CPI) implies that the Fed Funds rate should be:

5.4% + 0.5*0% + 0.5*(5.4%-2) + 2 = 9.1%

As Bernanke and many others have explained, you don’t want to take the Taylor rule literally, and the Fed raising rates to 9.1% Volcker-style at their next meeting would be a terrible idea. But keeping the Fed Funds rate under 0.5% would also be a terrible idea. Markets do expect the Fed to keep raising rates this year, but slowly, so that they would be around 2.25% by December. I’ll go on record as worrying that this is too slow, and recommending that they raise rates by at least 0.5% at their next meeting, and continue doing so until market-based measures of medium-run inflation are down to 2%.

Disclaimer: I’m a microeconomist whose last post on inflation was at best only directionally right. Consider this the view of one “insider-outsider” and then go read smarter people like Scott Sumner.

Inflation During the Pandemic in the OECD

Jeremy Horpedahl2 Comments

Inflation is definitely here. The latest CPI release puts the annual inflation rate in the US at 8.5% over the past 12 months, the highest 12-month period since May 1981. That’s bad, especially because wages for many workers aren’t keeping up with the price increases (and that’s true in other countries too).

But what about other countries? Many countries are experiencing record inflation too. The same day the US announced the latest CPI data, Germany announced that they also had the highest annual inflation since 1981.

Using data from the OECD, we can make some comparisons across countries during the pandemic. I’ll use data through February 2022, which excludes the most recent (very high!) months for places like the US and Germany, but most countries haven’t released March 2022 data quite yet.

Let’s compare inflation rates and GDP growth (in real terms, also from the OECD), using the end of 2019 as a baseline. We’ll compare the US, the other G-7 countries, and several broad groups of countries (OECD, OECD European countries, and the Euro area). The chart below uses “core inflation,” which excludes food and energy (below I will use total inflation — the basic picture doesn’t change much).

Continue reading →

It’s Still Hard to Find Good Help These Days

Zachary Bartsch2 Comments

Consumption is the largest component of GDP. In 2019, it composed 67.5% of all spending in the US. During the Covid-19 recession, real consumption fell about 18% and took just over a year to recover. But consumption of services, composing 69% of consumption spending, hadn’t recovered almost two years after the 2020 pre-recession peak.  For those keeping up with the math, service consumption composed 46.5% of the economic spending in 2019.

We can decompose service consumption even further. The table below illustrates the breakdown of service consumption expenditures in 2019.

I argued in my previous post that the Covid-19 pandemic was primarily a demand shock insofar as consumption was concerned, though potential output for services may have fallen somewhat. When something is 67.5% of the economy, ‘somewhat’ can be a big deal. So, below I breakdown services into its components to identify which experienced supply or demand shocks. Macroeconomists often get accused of over-reliance on aggregates and I’ll be a monkey’s uncle if I succumb to the trope (I might, in fact be a monkey’s uncle).

Before I start again with the graphs, what should we expect? Let’s consider that the recession was a pandemic recession. We should expect that services which could be provided remotely to experience an initial negative demand shock and to have recovered quickly. We should expect close-proximity services to experience a negative demand and supply shock due to the symmetrical risk of contagion. Finally, we should expect that services with elastic demand to experience the largest demand shocks (If you want additional details for what the above service categories describe, then you can find out more here, pg. 18).

Continue reading →

Deficits Are Here to Stay

Jeremy Horpedahl1 Comment

Last week President Biden released his Fiscal Year 2023 budget proposal. The annual release of the budget proposal is always exciting for economists that study public finance. The president’s proposal is the first step in the federal budgeting process, which in some cases leads to the full passage of a federal budget by the start of the fiscal year in October (though perhaps surprisingly, the process rarely works as intended).

This year’s budget is especially interesting to look at because it gives us our first look at what post-pandemic federal budgeting might look like. And while the budget has a lot of detail on the administration’s priorities, I like to go right to the bottom line: does the budget balance? What are total spending and revenue levels?

The bottom line in the Biden budget this year is that permanently large deficits are here to stay. Keep in mind that a budget proposal is just a proposal, but it’s reasonable to interpret it as what the president wants to see happen with the budget over the next 10 years (even if Congress might want something different). Over the next 10 years, Biden has proposed that budget deficits remain consistently right around 4.5% of GDP, with no plan to balance the budget in the near future.

How does this compare to past budget proposals? For comparison, I looked at the final budget proposals of Biden plus his two predecessors. I start Obama’s in 2021 to match Trump’s first year, and all three overlap for 2023-2026. I put these as a percent of GDP so we don’t have to worry about inflation adjustments (though we might worry about optimistic GDP forecasts, see below).

Continue reading →

Tradle

James BaileyLeave a comment

The success of Wordle has inspired a host of similar games. My personal favorite is Worldle, where you guess a country based on its shape. But the one that’s most econ-relevant and the one that I learn the most from is Tradle. You have to guess the country based on its exports:

This one would be a lot easier if I knew what Kaolin is

Its powered by data from the Observatory of Economic Complexity. I recommend checking that out after you try the game.

$5,000 Worth of Vaccines Saves One Life

Jeremy Horpedahl1 Comment

I’ve written about the social benefits (in terms of the value of lives saved) of COVID mitigation measures, such as wearing face masks, before. But at this juncture in the pandemic (and really for the past 12 months), the key mitigation measure has been vaccines. How much does it cost to save one life through increased vaccination?

Robert Barro has a new rough estimate: about $5,000. In other words, he finds that it takes about 250 additionally vaccinated people in a state to save one life, and the vaccines cost about $20 to produce (marginal cost). So, about $5,000.

Barro gets this number (specifically, that 250 new vaccinated people saves one life) by using cross-state regressions on COVID vaccination rates and COVID death rates. Of course, there are plenty of potential issues with cross-state regressions. It’s not a randomized control trial! But Barro does a reasonable job of trying to control for most of these problems.

Another way to restate these numbers: if we assume that the VSL of an elderly life is somewhere around $5 million, then the social benefit from each person getting vaccinated is around $20,000. In other words from a public policy perspective, it would have made sense to pay each person up to $20,000 to get vaccinated!

Or thought of one more way: each $20 vaccine is worth about $20,000 to society. That’s an astonishing rate of return. And we’re not even including the value of opening up the economy earlier (from both a political and behavioral perspective) than an alternative world without the vaccines.

Covid Evidence: Supply Vs Demand Shock

Zachary Bartsch4 Comments

By the time most students exit undergrad, they get acquainted with the Aggregate Supply – Aggregate Demand model. I think that this model is so important that my Principles of Macro class spends twice the amount of time on it as on any other topic. The model is nice because it uses the familiar tools of Supply & Demand and throws a macro twist on them. Below is a graph of the short-run AS-AD model.

Quick primer: The AD curve increases to the right and decreases to the left. The Federal Reserve and Federal government can both affect AD by increasing or decreasing total spending in the economy. Economists differ on the circumstances in which one authority is more relevant than another.

The AS curve reflects inflation expectations, short-run productivity (intercept), and nominal rigidity (slope). If inflation expectations rise, then the AS curve shifts up vertically. If there is transitory decline in productivity, then it shifts up vertically and left horizontally.

Nominal rigidity refers to the total spending elasticity of the quantity produced. In laymen’s terms, nominal rigidity describes how production changes when there is a short-run increase in total spending. The figure above displays 3 possible SR-AS’s. AS0 reflects that firms will simply produce more when there is greater spending and they will not raise their prices. AS2 reflects that producers mostly raise prices and increase output only somewhat. AS1 is an intermediate case. One of the things that determines nominal rigidity is how accurate the inflation expectations are. The more accurate the inflation expectations, the more vertical the SR-AS curve appears.*

The AS-AD model has many of the typical S&D features. The initial equilibrium is the intersection between the original AS and AD curves. There is a price and quantity implication when one of the curves move. An increase in AD results in some combination of higher prices and greater output – depending on nominal rigidities. An increase in the SR-AS curve results in some combination of lower prices and higher output – depending on the slope of aggregate demand.

Of course, the real world is complicated – sometimes multiple shocks occur and multiple curves move simultaneously. If that is the case, then we can simply say which curve ‘moved more’. We should also expect that the long-run productive capacity of the economy increased over the past two years, say due to technological improvements, such that the new equilibrium output is several percentage points to the right. We can’t observe the AD and AS curves directly, but we can observe their results.

The big questions are:

  1. What happened during and after the 2020 recession?
  2. Was there more than one shock?
  3. When did any shocks occur?

Below is a graph of real consumption and consumption prices as a percent of the business cycle peak in February prior to the recession (See this post that I did last week exploring the real side only). What can we tell from this figure?

Continue reading →