In Praise of the FRED Excel Add-in

Sometimes, large entities have enough money to throw at a problem that by sheer magnitude they produce something great (albeit at too high a cost). The iPhone app from the FRED is not that thing. But the Excel add-in is something that every macroeconomics professor should consider adding to their toolkit.

Personally, I include links to FRED content in the lecture notes that I provide to students. But FRED makes it easy to do so much more. They now have an add-in that makes accessing data *much* faster. With it, professors can demonstrate in excel their transformations that students can easily replicate. The advantage is that students can learn to access and transform their own data rather than relying on links that I provide them.

The tool is easy enough to find – FRED wants you to use it. After that, the installation is largely automatic.

Installed in excel you will see the below new ribbon option. It’s very user friendly.

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Russia, The US, and Crude Data

Overall, I’ve been disappointed with the reporting on the US embargo against Russian oil. The AP reported that the US imports 8% of Russia’s crude oil exports. But then they and other outlets list a litany of other figures without any context for relative magnitudes. Let’s shine some more light on the crude oil data.*

First, the 8% figure is correct – or, at least it was correct as of December of 2021. The below figure charts the last 7 years of total Russian crude oil exports, US imports of Russian crude oil, and the proportion that US imports compose.  That 8% figure is by no means representative of recent history. The average US proportion in 2015-2018 was 7.8%. But the US share as since risen in level and volatility. Since 2019, the US imports compose an average of 11.9% of all Russian crude oil exports.

As an exogenous shock, the import ban on Russian crude oil might have a substantial impact on Russian exports. However, many of the world’s oil importers were already refusing Russian crude. The US ban may not have a large independent effect on Russian sales and may be a case of congress endorsing a policy that’s already in place voluntarily.

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Reading Literacy Data

The story that I’ve heard is this:

            In the US, we care about education. We believe that all people should receive one, regardless of their family status. Therefore, states provide education directly.

There you have it. We provide education in the US so that everyone gets a more fair shake at education. We might disagree about the purpose of an education. Maybe it’s for improved job prospects, for a more informed citizenry, or for more unified values and experiences. One socially awkward answer is that state schools are, in part, a childcare service that permit parents to work. Except for these couple of reasons, school provision and compulsory education should, at the very least, increase literacy. That’s a low bar.

Given the above reasoning states began to pass compulsory school legislation. Massachusetts was first in 1852. Followed by DC and Vermont in the 1860s. Thirteen more adopted compulsory education legislation by 1880. By the year 1900, most states had compulsory schooling legislation on the books that was applicable to at least some age groups. See the figure. Thus, did the US achieve more equality, so goes the story.

The reasoning behind the story is sound. Without education of some sort, people will surely have less human capital. The vulnerability of the reasoning is that formal schooling is not the only form of education. A person who doesn’t attend school may help a parent at work or have a private tutor – or simply grow in a milieu of thoughtful exposure. Therefore, requiring that a child attend school may not improve human capital by a degree greater than what the child would have been doing otherwise. That’s an empirical matter.

The figure below illustrate the data for ‘white’ people and illustrates literacy between the ages of 20 and 30. Why that interval? At the lower end, we don’t have literacy data for people under the age of 20 in 1850 & 1860. On the higher end, any effects of compulsory schooling will only affect those who were children and subject to the law – older people are immune to compulsory schooling legislation.

The graph illustrates that state literacy rates were rising throughout the period. The main exception is 1870. Maybe the demands of the civil war caused children to work at home or otherwise and forego schooling. So the increase from 1870 to 1880 is more of a catch-up to a previous trend than anything else. While it’s true that several states passed compulsory schooling laws in the 1870s, that doesn’t explain the widespread literacy improvements across most states.

After 1860, we can examine the younger people who were subject to the schooling laws. The figure below for people ages 10-20 tells a similar story to the one above.

My biased reading of the data is that initial compulsory schooling laws had at least an ambiguous effect on the overall trend of improving literacy. I’ll delve deeper in future posts.

PS – The literacy data is from IPUMS.

PPS – The compulsory schooling law dates are allegedly from “Department of Education, National Center for Educational Statistics, Digest of Education Statistics, 2004.” But I couldn’t find the original source. Kudos to anyone in the comments who can find it.

Age-Old Dads

Do you know how old you are?

I’m 33. Specifically, I’m 33 years, 29 days old. I don’t know the time of day that I was born, but my mom probably remembers within a couple of hours. My dad did not keep track of my age. Growing up, it was normal for him to take me to a sports registration event and need to ask me for plenty of my details in order to complete the paperwork.

Do you know the age of your children? Is it normal for parents to lose track? Or is it just the dads?  …Or just my dad? I have no idea what is typical.

But I do have some decent evidence that, had my dad lived in 1850, he would not have been such an anomaly. Consider exhibit A: A histogram of US ages in 1850. The population was only about 23 million at the time and we have the age for about 19 million of those people. So the graph is relatively representative (IPUMS census data).

Do you notice anything weird about the graph?

That’s the question I asked my Western Economic History class.

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Aggregate Demand Regimes

Is inflation correlated with output growth?

Consider the AD-AS model which is often expressed in growth rates. Economists will often say that the short-run supply curve is flatter in the short-run and vertical in the long-run. In other words, aggregate demand policy can have SR output effects, and only has LR price effects.  Sounds good.

But there is a lot of baggage hiding behind “can have effects”. Often we’ll say that lackadaisical businesses cause a flatter SRS and that businesses with rational expectations have a vertical one. Also sounds good.

What causes the steepness of the SR supply curve? I’m sure that there are multiple determinants in regard to expectations. Here’s what got me on this topic. David Andolfatto shared the below graph and asked “Does lowflation necessarily mean low growth?.

Good question. My answer includes expectations concerning the monetary policy regime. Specifically, my answer was “It does in a regime of volatile and uncertain nominal income. Surprise AD growth pushes us up the SRAS.” Andolfatto called me out and in the right way, asking “What’s the evidences for this?


I had no evidence. I had the AS-AD model in hand and some logic – but no evidence. My logic is as follows. In a monetary regime that includes a constant rate of AD growth, output and price growth are inversely correlated. If NGDP grows at 5% always, then inflation falls when output growth rises. In other words, AD is exactly what people expect – illustrated as a vertical SRAS curve.

However, expectations are different in a regime of erratic AD. Let’s say that the rate of AD growth is unknown, but that the variance is known. If this is the world that you live in, then you make hay when the sun shines. Businesses sell more in periods of higher income. And, because they’re marching up the marginal cost curve, prices also rise. Alternatively, it may be that output growth is inflexible and prices rise as a goods are rationed.

Regardless of the truth, the above explanation is just story-telling. I had no evidence. What would the evidence even be? Here’s what I settled on. First, let’s express the AS-AD model in quarterly growth rates. In order to get a handle on monetary regime AD variance, I calculated the standard deviation of the NGDP growth rate by Fed Chair. Presumably, the Fed chair has a decent amount to do with monetary policy and the rear that occupies that chair is an indicator of when a regime begins and ends. I calculated the correlation between the GDP deflator and RGDP growth rates by regime. Below is the scatter plot.

What does it tell us? It tells us that regimes of stable AD growth experience a negative correlation between inflation and output growth. It also tells us that a AD growth volatility is associated with a positive correlation between inflation and output growth. So,  Does lowflation necessarily mean low growth? It does in a regime of volatile and uncertain nominal income.

(Of course this is all casual. It makes sense to me at first blush though. Having said that, the line of best fit also looks like it’s driven by the 2 extremely variable times: McCabe & Powell.)