Author: Zachary Bartsch

In Praise of the FRED Excel Add-in

Zachary Bartsch2 Comments

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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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.

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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).

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Amazon Credit Card Rewards

Zachary Bartsch4 Comments

I have a credit card that gives me rewards. I get a nice 5% cash-back on purchases from Amazon and a lower cash-back rate on other purchases. Sometimes, there are promotions that provide a rate of 10% or even 15%. But what are these rewards worth?

To simplify, there are two reward options:

Option 1 adds to my Amazon gift-card balance. It’s attractive. When I’m checking out at Amazon, it shows me my reward balance and it also shows me what the total cost of my purchase could be if I applied the gift card. It’s like they’re trying to pressure me to redeem my rewards in this particular way.

Option 2 is simply to transfer my rewards as a payment on my credit card or as a credit to my bank account (for the current purposes, they’re identical). Either way, the rewards translate to the same number of dollars.

Say that I spend $1,000 at Amazon. Whether I choose option 1 or 2 has value implications.

Option 1

The calculation is simple. If I spend $1,000 at amazon this month, then I can spend another $50 in gift card credits at Amazon next month. That’s the end. There are no more relevant cashflows. I used my credit card one month, and then was rewarded the next month. The only detail worth adding is the time value of money, which at 7% per year*, yields a present value of rewards at $49.72. Option 1 is nice in the moment. It’s so enticing to have a lower Amazon check-out balance due.

But you should never select Option 1.

Option 2

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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?

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This Time was Way Different

Zachary Bartsch5 Comments

The financial crisis recession that started in late 2007 was very different from the 2020 pandemic recession. Even now, 15 years later, we don’t all agree on the causes of the 2007 recession. Maybe it was due to the housing crisis, maybe due to the policy of allowing NGDP to fall, or maybe due to financial contagion. I watched Vernon Smith give a lecture in 2012 in which he explained that it was a housing crisis. Scott Sumner believes that a housing sectoral decline would have occurred, and that the economy-wide deep recession and subsequent slow recovery was caused by poor monetary policy.

Everyone agrees, however, that the 2007 recession was fundamentally different from the 2020 recession. The latter, many believe, reflected a supply shock or a technology shock. Performing social activities, including work, in close proximity to others became much less safe. As a result, we traded off productivity for safety.

The policy responses to each of the two were also different. In 2020, monetary policy was far more targeted in its interventions and the fiscal stimulus was much bigger. I’ll save the policy response differences for another post. In this post, I want to display a few graphs that broadly reflect the speed and magnitude of the recoveries. Because the recessions had different causes, I use broad measures that are applicable to both.

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Russia, The US, and Crude Data

Zachary Bartsch4 Comments

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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Two Decades of Real Estate Data

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Total spending on real estate construction has been rising since 2011. By 2016 it had reached its previous 2006 peak. However, total spending on *residential* real estate construction didn’t reach its previous 2006 peak until November of 2020. The graph below also includes the proportion of residential construction spending (Green). It has been rising since 2009. In and of itself, nothing is good or bad about this figure. We might be spending less on non-residential construction because we are getting better at using less land per unit of good or service produced. Or, it could be that our real investment in future production is falling relative to our current residential consumption.  Regardless, the share of residential construction hasn’t been at this level since 2003.

https://fred.stlouisfed.org/graph/?g=MzwL
https://fred.stlouisfed.org/graph/?g=MzwQ

Importantly, the difference in spending has not been driven by different construction costs. Both residential and non-residential construction costs have moved in tandem since 2010. Therefore, the rise in residential construction spending is not merely nominal – a greater proportion of resources are being consumed by residential construction. Indeed, real residential construction is up about 25% from 2019. The figure below illustrates real residential and nonresidential construction.

https://fred.stlouisfed.org/graph/?g=MzwU

That figure requires a double-take.

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Inflation Empirics

Zachary Bartsch2 Comments

Way back in the late 1970s and early 80s, Kydland and Prescott proposed rational expectations theory. This line of research arose, in part, because the Phillips curve ceased to describe reality well. Amid increasing inflation, people began to anticipate higher prices to a relatively correct degree when making labor, supply chain, and pricing decisions. Kydland and Prescott argued that individuals understand the rules of the game or how the world works – at least on average.

An increase in the money supply would increase total national spending, and increase demand for goods. However, firms also experienced increasing revenues and demanded more inputs such as commodities, capital, and intermediate goods. Because there were no greater productivity earlier in the supply chain, price roses. Firms began to understand that greater demand would eventually find its way to causing greater costs. Therefore, firms began raising prices before the cost of resources rose, increasing their willingness to pay for inputs and, ironically, hastening the increase in input prices. As a result, increases in the money supply began having substantial short-run price effects and negligible output effects.

However, assuming that people understand the rules of our economic system and ‘how the world works’ is hard to swallow. It is not at all clear that the typical economist understands monetary theory, much less clear that the typical person has a good understanding. Fortunately, another theory of expectations can help carry some of the load and achieve similar results.

Adaptive Expectations

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Asymmetric Liability, Common Law, & Urbanization

Zachary Bartsch1 Comment

Tort law is interesting. You can argue that someone harmed you, and you can cite almost no legislation in the process. Torte law in the US uses case law – the precedent set by previous rulings in the context of social norms. But, what cases did the early cases cite? They also cited earlier cases and social norms, though we may no longer have a record. The beauty of tort law it allows for changing relative costs in prudence and negligence.

Can you imagine a legislature attempting to codify the appropriate amount of neglect by, say, a painter? The standards would quickly go out of date. The relative cost of resources including labor, communications, materials, and the price differences among competitors of differing quality all change over time. Multiply these factors by 20 and then again by the number of occupations and regions in a country. You will quickly see that legislating the appropriate degree of prudence and neglect through congress is a fool’s errand. The challenge is too complicated and the world changes too quickly. In fact, attempting to legislate definitions for neglect and prudence could even backfire and result in regulatory arbitrage, which occurs when firms comply with de jur rules while avoiding them de facto.*

Externalizing Costs

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