To recap, there are four main inflation risks lurking over the U.S. economy.
A large tax cut could help fuel demand.
Tariff wars are only in a ceasefire, and high tariff rates (particularly for Chinese goods) might resume after the ceasefires expire.
A widening of the war might result in a crude oil spike.
Widespread deportations are cutting off some industries from labourers, particularly the agricultural industry.
I managed to not notice a curling rock in my path when sweeping on Monday, so my writing plans this week were curtailed as I nurse my left knee. As such, I am stuck with following the herd on Bluesky. My consulting work schedule has still been intense, but I think it should slow down shortly, giving me more editing time for my manuscripts.
One of the current Bluesky points of discussion is whether tariffs are “inflationary,” a “one-time price shock,” or even a “relative price shift.” I think that if we do see a large universal tariff hike, it would qualify as “transitory inflation.” As we have seen, transitory inflation is no big deal politically.
Editorial note. This article is an unedited excerpt that is the last section of my inflation manuscript. I have been sitting on that manuscript for a long time, as I was not completely satisfied with the final chapter that discussed the post-pandemic inflation surge. (The bulk of the book are primers discussing the basics of inflation, and the wacky theories you see from the inflation nutters in financial/economic commentary.) I think I still need to compress the final chapter’s text, but it is getting close to be ready for external editing. This article is a fairly lightweight discussion of current events, but I expect it to be read by people years from now, so delving into details of the election are not really needed.
I am also throwing in the towel on my Twitter presence. I have not spent much time reading social media or other blogs (mainly Subtstacks now) due to being overrun by projects, but I need to re-build my social media presence before trying to market my new book. With Musk throttling links to Substack, Twitter is effectively dead as a marketing tool. Anyway, I think Blue Sky is building up a critical mass, so I am now going to pay more attention to it: @brianromanchuk.bsky.social
I have been racking up a lot of consulting hours recently, so my writing has been on a back burner. I have also been looking at my two manuscripts (the inflation book, and the banking primer), without having new content to publish here.
I have decided that I am not going to add new content to my banking primer. I need to consolidate all my “banking theory” pieces into one or two chapters, and that would make the book at my target length (novella, not novel length). Rather than tackle that now, I have turned back to my inflation manuscript. The advantage of a being a long time separated from the text is that I can read it as a “new” text. This makes it much easier to edit — I have to re-read what I wrote, and mangled text stands out much better in text that I have been recently rewriting. It also made me happier with the manuscript when compared to when I was last heavily revising it.
The chapter that probably still needs the most attention is the last one — the discussion of the post-pandemic inflation kerfuffle. Until that chapter, the text reflects my attitude towards inflation that I had when I was working in finance: developed country inflation post-1990 is generally boring. Although I am not attempting to do a forecasting exercise in a book, it could easily be somewhat embarrassing to publish a book whose theme is “inflation is boring, actually” when the economy is in the process of entering some secular inflationary maelstrom.
def sooper_sekrit_inflation_forecasting_model(**kwargs):
"""
Proprietary inflation forecasting model.
So proprietary that the function arguments are themselves proprietary.
:param kwargs:
:return:
"""
return 2.0The above code snippet is a variant of one of my standing jokes: my proprietary one year ahead inflation forecasting model that just return 2%. The ugly reality is that this model outperformed most of the inflation forecasting models I had the misfortune of having to look at (so long as the look-ahead period is 12 months or more, so that a model cannot take advantage of known information when computing the 12-month rate-of-change).
The pandemic blew up that forecasting model, albeit there are not a great number of independent 12-month intervals after 2020. If we look back at the chart at the top of this article, headline inflation is back at fairly “normal” levels for the post-1990 period. Median inflation remains elevated (where it was in 1990, which was before inflation stabilised near the 2-2.5% level (depending on which inflation measure you use, CPI tended to be higher than PCE).
I have not yet started digging through charts of updated data, but my educated guess is that the housing component of CPI “explains” the stickiness of median CPI. That is, the inflation story is now largely one about housing (which is directly measured via rents, but house prices presumably influence rents).
The difficulty with dealing with housing inflation is that the internet is filled with people who have very strong opinions about the subject (to the point of it defining their online personality). I have reached the stage in life where I am not going to pursue the details of what Californians are doing to themselves in housing regulation. All I can offer is the insight is that housing inflation is high, and it may or may not come down over the coming decade.
But if we make the possibly incorrect assumption that rents cannot outstrip wages for a decade, inflation movements returns to being a business cycle story. The non-housing part of the economy seems to be closer to the 1990-2020 norm, although the spectre of a structurally tighter labour market (courtesy of demographic trends) remains to keep the inflation worriers scared this Halloween season. Although I was historically an inflation dove, I did see the story about a ageing population raising the dependency ratio being a plausible driver for changing the long-term inflation trend. (Admittedly, one can go look at all the failed “Japan is heading towards hyperinflation!” stories to see that demographics is not necessarily destiny with respect to inflation forecasting.)
The problem with the “structurally tight labour markets will lead to higher inflation” story is that business cycles move faster than structural trends. We got a big inflation pop in 2020 that can be tied to tighter labour markets — but that pop required a lot of short-term shifts all pointing in the same (higher inflation) direction. Outside the panicked pandemic reactions, governments and firms have time to react to changing labour market conditions. Modern management has gotten extremely aggressive in wasting workers’ time in practices like gig work, and so there is a lot of malinvestments to be culled in response to a relative price shift in workers’ favour. And policymakers will react to inflation target misses (with the primacy of monetary or fiscal policy left to the readers’ preferences), so policy should be expected to lean against inflation overshoots. (Inflation was left below target in the 2010s, but nobody really cared, and the attempts to use monetary policy to nudge inflation upwards was just a classic string pushing exercise.)
Admittedly, my benign inflationary outlook does face an immediate risk — in the United States at least. Although I have done my best to avoid discussing the upcoming American Presidential election (out of deference to my cardiovascular system), it is clear that some of the err, wackier, economic proposals that have been floated by one major candidate might disrupt the economy. Obviously, I will have time to react to this before the manuscript is finally published.
The other angle to the text I need to revisit is the “transitory debate.” Although I might just grab some articles that fit my priors, I think the debate can summarised as possible.
If we define “transitory” as inflation immediately returning to “normal” levels, it was not transitory. However, this is certainly not how I interpreted “transitory.”
The definition I leaned towards was that inflation would return to “normal” levels without requiring a recession or much higher inflation. Although this definition seems weak, it is in opposition to the possibility of entering a phase of structurally rising inflation (like the 1970s).
One camp of people argue that “inflation was not transitory” because central banks raised interest rates to reduce it. However, this requires the belief that interest rates control inflation, which is not easily falsified. This episode can be explained by central bankers following their historical practice of setting the policy rate at a lag to inflation trends. Such behaviour will always results in the policy rate peaking just before transitory inflation spikes reversing. Since I am not an interest rate believer, this is not a definition I would use.
I should have more time to devote to writing. Although I should be focussing on getting my manuscripts out the door, I might be putting up some updated inflation charts as part of a post-mortem on the pandemic inflation spike.
One of the advantages of being very slow to finish off my inflation manuscript is that I can add content as things pop up. This section is an edited draft that was added in response to a recent Felix Salmon article.
One argument that came up as I was finishing this manuscript is that there has been a linguistic drift in the word “inflation.” In the article “’Inflation Doesn’t Mean What is Used To,” Felix Salmon argued that in popular usage, the meaning of “inflation” has drifted to mean: “[A]m I paying higher prices for things than I used to?”
Although Salmon’s article (correctly) predicted that economists’ responses to this suggestion would be negative, he argues that they are out of touch with the common usage of the term. Since this book intends to properly explain the concept of inflation, there is no way I could use such a definition, since it has obvious shortcomings. (As he noted, prices could be falling, but this would qualify as “inflation” so long as prices were lower at some previous point in time.)
If we rely on what prices are stuck in people’s memory, the results can be dubious, since the comparison points are arbitrary. My personal example is when I visited the United Kingdom in 2022 and compared the prices of chocolate bars to the price in the department vending machine in 1992 (22 pence, or 23 pence for the premium bars). (That price stuck since I used to feed my 1p and 2p coins into the vending machine to get rid of them.) The fact that prices were indeed lower 30 years previous is not providing much information about current trends in the U.K. economy.
Although I have doubts that this new usage would get traction – any serious economist or financial market commentator is not going to use it – there are a few arguments that seem reasonable.
1. Salmon highlights that the use of the change of the price level over one year is arbitrary. However, using the one-year percentage change has major advantages over alternative time frames (discussed below). People write “inflation” or “inflation rate” instead of “annual inflation rate” because it is less wordy.
2. Most people in developed countries at present do not have a good grasp of what the overall inflation rate is, and mainly look at the level of prices of a handful of goods (gasoline, groceries). They will then compare current prices to some conveniently lower price that occurred some time in the past. However, I would argue that is a side effect of the low inflation regime – back in the 1970s, people had a much stronger grasp of inflation since they dealt with increasing inflation rates over a multi-year period. The fact that people apparently paid money to a website that claimed that inflation was “really” several percent higher than official statistics is a sign that many people do not have a good idea what the inflation rate is.
3. Although not noted in the article, people’s perceptions of inflation seem to be partly driven by the editorial agenda of the business press. It is not entirely an accident that the Republican-leaning business press got extremely excited about inflation during the presidential term of a Democratic President.
The preference for the annual rate of change of inflation is easily explained. The first is that it eliminates seasonal effects. The second is it easy to calculate – how many people would know how to properly calculate the annualised rate of inflation over periods other than one year? The final reason is that the one-year rate of change seems to capture changes in economic trends. Annualising 3-month percentage changes creates massive swings in the inflation rate that are misleading (particularly with data that has seasonal adjustment problems or even unadjusted). A two-year annualised inflation rate (or longer) might be useful for historical analyses (what happened over a certain period?) but moves too slowly to capture changes in economic trends. Although it is not clear that a 12-month window is “optimal,” it is the easiest one to understand. (Why would you look at the annualised percentage change over 9 months?)
Although it is safe to say that the popular perception of inflation is quite often at odds with official inflation, it seems unlikely that changing the definition of inflation would help matters.
This is a sub-section that I forgot to include in my previous article that discussed inflation and financial assets. This is for a section of my manuscript that replaced two problematic sections. I kept this new section as lightweight and brief as possible; I might add more content later.
Currency trading is somewhat unusual in that the price reflects what is happening in two different currency zones. If we want to discuss how currencies relate to inflation, we should keep in mind that we should be talking about the inflation rate in the two currencies. For example, if the inflation rate in Canada is 2% and the inflation rate in the United States is also 2%, the effect of inflation on the Canada-U.S. exchange rate should cancel out.
The beauty of the Cantillon Effect is that it gives a simple relationship between inflation and financial asset markets. Allegedly, people who somehow get “new money” first rush out and buy financial assets, driving up their price. This then leaks out into consumer prices. The problem with simple rules related to financial asset prices is: why are the people who discovered them all getting rich using them?
Even if one believes that asset price increases represent inflation, the general reaction among North American central bankers would be to think you are crazy if you think asset prices should be included within an inflation target mandate. (I am less sure about the reaction of Continental European central bankers.) Although they might accept that exuberance in financial markets should be toned down, targeting asset prices directly poses many problems.
I was recently on a podcast with Steven D. Grumbine to discuss inflation. Link: https://realprogressives.org/podcast_episode/episode-268-there-is-no-magic-pricing-fairy-with-brian-romanchuk
The podcast description from the webpage is.
“Inflation is always and everywhere a monetary phenomenon, in the sense that it is and can be produced only by a more rapid increase in the quantity of money than in output.”
Milton Friedman
This quote by the grandaddy of neoliberal economics is from 1963. Some in the mainstream have been dining out on it ever since.
According to our guest, author and blogger Brian Romanchuk, neoclassical economics relies on mathematical models and fail to capture the complexity of real-world inflation. He highlights the importance of understanding the supply and demand dynamics in setting prices and explains that inflation can be influenced by factors such as supply chain shocks and changes in the labor market.
Brian also points out that it’s not enough to blame inflation on corporate greed; after all, corporations are always driven to maximize profits. He mentions the Cantillon effect, which suggests that the first recipients of newly created money benefit from inflation as prices go up, while the poor and working class bear the brunt of higher prices down the road.
Brian and Steve discuss inflation constraints on fiscal policy. Brian argues that while extreme fiscal policies could lead to inflation, most of the time, fiscal policy is relatively moderate and does not have a significant impact on inflation. They criticize the government for not trying to set prices and argue that the government often follows the private sector’s lead, making things worse.
This is a discussion of some topics around inflation. Although some of the discussion related to the concerns of my book, a lot of it relates to some of the recent political economy controversies with inflation. It was fun, although I am not sure how well suited I am to the podcast format.
Otherwise, I have been plugging away at fixing weak points in my inflation manuscript. Rather than waste reader’s time by rushing out some random comment, you are encouraged to get your dose of Romanchuk (and Grumbine) content via the podcast.
One fundamental problem with the consumer price index is that it is the result of what most people would consider a complex calculation. This should not be surprising, since they are tasked with converting the price change of large number of items (80,000 items in the United States) into a single monthly index percentage change. People who are mad about the price of eggs going up generally just look at the price of eggs, they do not want to hear academic jibber-jabber about 80,000 items or (oh dear) a Laspeyres formula.
In this section, I am not going to attempt to explain the formulae used by the national statistical agencies. Anyone comfortable with reading those equations either know the answer already or would be sensible enough to go to the source agency rather than rely on me not mangling the equation during the editing process. Instead, I will explain the fundamental issues that we see in the simplest possible price index: one with two types of apples. A reader might immediately ask: why use two types of apples, and not apples and oranges (which I used in the first draft)? The explanation for that choice is given later, but the short answer involves not mixing up apples and oranges.
I want to warn readers that they should not spend time attempting to find logical flaws with my “index” calculations. I have come up with examples that I believe give a good feel for the underlying economic issues, but I can think of at least one way of “breaking” a suggested calculation by playing around with the numbers. Statistical agencies use more complex formulae than I use, and if you want to nitpick, you need to look at those formulae.
But before we get to simplified index calculations, we need to address why we need consumption weights in the first place? Why not just look at the price of a fixed basket of goods?
The most intuitive price index is one that corresponds to a fixed basket of goods. (Price indices also include services. But I will just write goods in this section since I do not want to have to write “fixed basket of goods and services.”) The idea is straightforward: if you buy the same goods at different times, how much does the price change? One whimsical version of this index is “The PNC Christmas Price Index.” This is an index that tabulates the cost of buying the items listed in the song “The Twelve Days of Christmas” (with a certain amount of imagination needed to determine prices for things like “10 lords-a-leaping” in the non-aristocratic United States). One might run into indices of this type in economic history, where researchers are attempting to summarise price trends in earlier eras when the CPI was not calculated.
To give an example that will be used in the rest of this section, imagine a price index for a subset of fresh fruit that just includes Cortland Apples and Empire apples. (These are two popular varieties of apples that are grown in Quebec, I have no idea whether readers elsewhere are familiar with them.) Although not too many people would be interested in such an index (other than apple lovers), this might be a sub-index of a larger index. We then assume that a household buys 30 apples of each type each month.
If the price for these applies conveniently start $1 at each, then the starting price for the total fruit basket is $60. We could strip the dollar sign out of the quoted number and say the price level is 60.
Let us then imagine that the price of Empire apples doubles to $2, but the Cortland ones remain at $1. Then the cost of the basket is $90 ($60 for the 30 Empire, and still $30 for the 30 Cortland). This is a 50% increase, which makes sense. Previously, there was a 50/50 weighting between Empire and Cortland, and so the overall inflation rate is a 50/50 weighting of the two percentage changes (100% and 0%).
If you wade through complaints about rising prices not being reflected by the CPI, most of what you see are effectively complaints about weightings. People mad about price increases just want to talk about those price increases, and do not want to discuss other goods and services whose prices did not rise. In the previous example where Empire prices doubles but Cortland were unchanged, one would be ensured that there will be hundreds of angry people on the internet discussing Empire apple prices, but not Cortland. Even though the price index rose by 50%, that is not good enough because that does not match the 100% Empire price rise.
Although one might feel sad for fans of Empire apples, we need to accept that macroeconomics is the study of overall behaviour. Although the fixed basket of Cortland and Empire apples is imperfect (for reasons to be discussed), it at least is supposed to reflect an economic concern of households: how much am I spending on apples?
As such, we need to have some means of weighting the different percentage price changes into an average price change. When we look at how price indices are used, we need to have the weighting set so that they reflect the overall consumption of households.
We can then return to the question of having a “fixed basket”: always have the same number of items purchased each month? If we buy the same things every month, why not just add up their cost (like in my example)?
The immediate response to that question is that my example “index” is misleading, as it consists of generic fresh fruit that appear somewhat timeless from the point of view of consumers who are not particularly concerned about the histories of apple varieties. If we jumped to things linked to technology, problems with fixed consumption baskets are obvious. For example, renting VHS video cassettes was an extremely common expenditure item in the 1980s. At the time of writing, it is extremely hard to find stores that rent even the successor technology to VHS cassettes – Digital Video Discs (DVDs). Conversely, cellular data plans are a feature of most families’ budgets, and such plans did not exist in the 1980s. Any attempt to create a fixed basket of consumption goods is eventually going to look laughable in modern industrial capitalist societies.
One might say that this is true for technology goods but is not true for non-processed foods. Why not have a fixed basket for those items? (One crank made exactly that argument on social media just before I wrote this section.) Even if we want to skate over awkward questions like how food with “organic” designations fit in with food when those designations did not exist, consumption weights change (admittedly slowly). North America consumption of quinoa was negligible in the 1970s. Coffee selection is vastly improved in North America since the 1980s, and grocery coffee purchases are increasingly weighted towards coffee pods.
Although whole foods are a convenient category that seems comparable over time – Statistics Canada has a section breaking out the prices used for selected ones as part of its CPI release – they are an increasingly small weighting in consumer budgets in developed countries. You can find other “generic” goods and services – natural gas, gasoline (sort of, blends change), hair cuts – but they are in scattered categories. To be useful, we need to make periodic surveys of consumption to get weights that reflect what people are actually spending money on.
If government statisticians tracked every single transaction in the economy, they would know exactly the current consumption spending weighting of consumers. The problem is that they do not have access to that information. It is time consuming (and expensive) to survey consumers to get detailed breakdowns of their consumption. (By contrast, getting price data is relatively easy – just send government employees into stores to see what prices are posted.) Consumption surveys are done at a lower frequency. The U.S. Bureau of Labor Statistics describes the weighting situation as:
The CPI measures the change in the cost of goods and services purchased by consumers from one period to the next. Household spending weights are used to average the changes in component goods and services into the All-items index. In the first 50 years of producing the CPI, the BLS updated the spending weights roughly every 10 to 15 years based on spending information collected in periodic household surveys. In the 1980s the Consumer Expenditure Surveys (CE) became continuous and the BLS began updating the CPI spending weights every two years, starting in 2002, when the CE sample was increased to support more frequent weight updates.
(Taken from the 2022 CPI Weight Update information: https://www.bls.gov/cpi/tables/relative-importance/weight-update-information-2022.htm.)
An update frequency of every two years might not sound too bad, but there is a fundamental problem: consumption patterns will shift based on price changes. For readers who are fans of free market capitalism, one of the selling points of the system is that households and firms change behaviour based on price signals. If the price of Empire apples doubles, you are supposed to say to yourself “Maybe I will replace my intake of relatively expensive Empire apples by Cortland apples.” If we had monthly surveys of consumption weights that updated in line with prices, we would know how much substitution happened. But we do not, and so economists need a methodology to make a guess how much substitution occurred.
Although most of us accept that we are stuck with making an educated guess for substitution, this is a topic gets some people mad. By an amazing coincidence, the people who are most mad about assuming that consumers substitute away from goods that jumped in price are pretty much the same people who insist that free market capitalism is great because of price signals. (I will be dwelling on this point multiple times in this book, since it is shows up in a variety of complaints.)
I will now look at possible alternatives to what happens in response to the Empire apple jump.
If we wanted to reduce the reported rate of inflation, we could assume that consumers substitute completely away from the relatively expensive apples. Instead of buying 30 Empire and 30 Cortland, they could just buy 60 Cortland apples. Since we assumed that Cortland prices are unchanged at $1, the total consumption is unchanged at $60. This is a 0% inflation rate (matching the inflation rate for the Cortland variety).
Of course, this outcome does not match the description of the fixed consumption basket – since the number of each item changed. Instead, we have a situation like the commonly used price indices (like the CPI): we are tracking the cost of a category of goods (apples within fresh fruits) over time. Since we no longer are buying a fixed basket of goods, we really should not put a dollar value on the index. Instead, we are looking at the percentage change in the price of buying two varieties of apples over time.
Since we are not using a fixed menu of purchase amounts, we are always working with relative prices. To calculate the percentage change on the overall basket, add up the percentage changes of each item multiplied by their assumed weight in the monthly purchase basket. In the case of total substitution, we have a 0% weight on the 100% change in Empire prices plus a 100% weight on the 0% change in Cortland prices. In the fixed basket example, there is a 50% weight on the two price changes, giving the 50% overall inflation rate.
However, assuming consumers always stop purchasing goods whose prices rose the most would be as silly as always putting a 100% weight on the fastest-rising prices. (In fact, there are some logical problems with such a situation. What happens if Empire apples were unchanged the next month, while Cortland apple prices doubled?) We need some magic way to split the difference.
We then let some economists loose to come up with a model that gives us an updated consumption weight that is a function of relative price changes. (If every single item in the sub-index has the same percentage change, the weighting does not matter.) If you want to go through the literature, there will be a lot of jargon discussing the models. My expectation is that the reader is not in charge of developing new price indices, and so I see no need to delve into this jargon.
Since I am lazy, I will assume that the model output conveniently hits the midway point between the two previously discussed cases. This is purely a literary assumption – actual models used in practice will have different weighting shifts based on the data.
If we assume that consumers split the difference and buy 45 cheap Cortland apples and 15 expensive Empire ones (instead of 30/30), the total cost of the basket is now $75. This is 25% higher than the previous basket price of $60. This 25% inflation rate is determined by having a 75% weight on the Cortland price change, and a 25% weight on the Empire price change.
If we want to think in terms of the prices of baskets of goods, the inflation rate that is calculated is not the change in the price of the old basket of goods in the current period. Instead, it is the change in the price of the current basket of goods versus buying that new basket at the old prices.
This is not how people who get mad at inflation statistics want to think. They invariably present price changes based on buying the old basket of goods at current prices, rather than what being based on what it would have cost to buy the current basket at the old prices.
To the extent that price spikes represent shortages, we also have the problem that substitution must happen. If Empire apple prices spiked because there was a highly selective crop failure, there are less Empire apples to buy. The volume of Empire apple purchases must fall. That said, this is trickier to apply to globally traded goods. There might be a shortage of oil at the global level, leading to a price spike on oil markets, but a rich country might keep importing the same amount and keep consumption unchanged.
We only would know how much substitution there was if we had access to monthly consumption data (which we do not).
We can then ask ourselves: if apple prices have a high relative price shift, why would consumers not get their fresh fruit fix by buying oranges? That is, we could assume that consumers will substitute spending based on relative price shifts within the wider fresh fruit category.
This is a possibility that creates a lot of complaints about CPI, based on people not paying attention to the actual calculations. The CPI calculations generally do not allow for substitution across item categories. To quote Greenlees and McClelland in “Addressing misconceptions about the Consumer Price Index”:
To begin, it must be stated unequivocally that the BLS does not assume that consumers substitute hamburger for steak. Neither the CPI-U, nor the CPI-W used for wage and benefit indexation, allows for substitution between steak and hamburger, which are in different CPI item categories. Instead, the BLS uses a formula that implicitly assumes a degree of substitution among the close substitutes within an item-area component of the index. As an example, consumers are assumed to respond to price variations among the different items found within the category “apples in Chicago.” Other examples are “ground beef in Chicago,” “beefsteaks in Chicago,” and “eggs in Boston.”
I used the non-intuitive “Empire versus Cortland apples” instead of “apples versus oranges” because the U.S. CPI calculation does not allow for substitutions across apples and oranges, only within “apples.” However, this is not going to hold for every price index, as they may allow for substitution effects within categories like fresh fruit.
At the higher level, one might ask whether people substitute across much different categories. If movies get more expensive, will they instead buy a video game? Although people always need to eat, they can do things like eat at home instead of at a restaurant.
To the extent that price indices do not allow substitution, they are going to overstate the true cost inflation experienced by households who react to price signals. This partly explains the massive disconnect between the mainstream economists that argue that the CPI overstates inflation versus the commentators who insist that CPI inflation rates understate inflation.
Another issue that pops up in index calculation is that we might have a price for a good or service in one month, but not in another. This could be the result of data gathering issues, outright shortages, a product coming into existence – or being pulled from the market.
Since we only have a price for the good or service for one month, we cannot give a percentage change in the price. One would need to dig into the methodology handbook to see how each statistical agency deals with this.
However, there is an interesting philosophical issue created by new product launches. In an environment of rising wages, it is easy to see how new product offerings might be “luxury” versions of existing ones.
One example that comes to mind is the evolution of take-away “coffee drinks” in North America from mainstream venues. Back in the Good Old Days (i.e., when I was a kid), North Americans mainly just bought plain coffees from restaurants/doughnut shops. By the 1980s, you had an infiltration of cappuccino and espresso and so forth in mainstream restaurants. Later on, we saw the rise of “iced coffee drinks.” Each of these evolutions had new beverages coming out at higher price points relative to the existing drinks.
Even though the prices of standard coffees might not have risen by much, switching to the new drinks meant that consumers were paying more money for the same amount of caffeine buzz. This allowed restaurants to grow their nominal sales, even though the stores might have had the same overall volume of customers.
This leads to one of my personal inflation theories. When we look at the late 1990s, the economy was buoyant, but the bears were mystified: where is the inflation? My reading of the situation was that companies were able to absorb increased nominal demand by pushing out luxury brands. This worked until the pandemic, where product innovations were not enough to absorb the nominal demand.
It would be very easy to drown in jargon and mathematical notation when looking at conventional descriptions of price indices. Most of the internal debates among economists refer to complex assumed behaviour. But it is possible to see how price index calculations run into rather awkward questions by just looking at what happens with a basic example.
Detailed discussion of price index construction is best found at the methodology guides of national statistical agencies. Example references are listed in Section 1.2.
The PNC Christmas Price Index has been calculated by the PNC Financial Services group for over 40 years. It has a web page found at: https://www.pnc.com/en/about-pnc/topics/pnc-christmas-price-index.html
Greenlees, John S., and Robert B. McClelland. “Addressing misconceptions about the consumer price index.” Monthly Labor Review 131 (2008)
My manuscript is somewhat unusual in that I am mainly discussing the “known properties” of inflation, without offering a theory of inflation. The more usual situation is that people have extremely strong views on what explains inflation (and more often than not, these views contradict “known properties” of inflation). I decided to not cover inflation theories on the basis that it somewhat difficult to get good introductory information due to the huge mass of disinformation. By avoiding theory, the manuscript statements are relatively safe to make, and so my manuscript itself hopefully stays out of the “disinformation” category.
A popular belief in hard money internet commentary is that economists are conspiring to lower reported inflation. The advantage of this is to mislead voters and to reduce cost-of-living adjustments paid by the government. Admittedly, there are cases in emerging markets where there is widespread skepticism about government inflation statistics, and the government inflation numbers do not appear to align with market data. As such, I label this as a “misunderstanding,” as I accept that CPI numbers probably have been fudged somewhere. However, the usual case in developed countries is that statistical agencies are transparent about their methodologies, and the complaints are bad faith misinterpretations of the methodologies.
The usual response to critics who state things like I just did is “give me a better model.” The idea is that we need to replace one reductionist model with another reductionist model. The reasoning seems to be that economics is like physics, where a lot of the history of the field is doing exactly that. (Physicists might be getting into “complexity,” which may or may not be a mathematical pseudo-science. In any event, this is not what people have in mind when they compare economics to physics.) If inflation is a complicated process, any reductionist model is going to fail.
Any empirical work on the link between inflation and the labour market is going to run into a snag that is the result of what I argue are relatively non-controversial positions.
We assume that there exists a unitary variable that summarises the business cycle — which might not be directly measurable. It might be something like the first principal component of a few underlying variables. The usual measured variable that is supposed to be a proxy of this variable is GDP, but one may note that the NBER looks at a variety of variables to date recessions. The justification for the existence of this variable is that recessions are a somewhat nonsensical concept without the notion of some way of summarising the state of the business cycle which goes up and down. (If one wants to insist that no such unitary variable exists, we end up with business cycle nihilism. This might be the correct stance, but makes it very awkward to discuss macro.)
Inflation is a pro-cyclical variable, possibly with a lag. This can be justified by eyeballing inflation/GDP charts. There are any number of theoretical stories justifying why this is the case.
Employment growth is pro-cyclical, almost by definition. Rising unemployment is one of the defining characteristics of a recession.
(Core/median) inflation and employment growth empirically exhibit “trends” — although monthly data might be noisy, the averages across months tend to be smoother after seasonal adjustment (albeit with step changes during things like recession).
As an added bonus, we can note that private sector credit is pro-cyclical. This can be seen by eyeballing charts, and is likely to be a component of any model that takes the Kalecki Profit Equation seriously. (Neoclassical models notably do not.) Bank lending and hence deposits are a component of private credit, and thus the bank deposit component of M1 is going to be pro-cyclical.
You do not need a doctorate in statistics or need to study Real Analysis to know that 1-4 taken together imply that inflation and employment growth are going to be correlated to some possibly unknown “business cycle” variable. It is going to be nearly impossible to detect a causal relationship between the variables unless the relationship is simple and stable over time. Guess what? We cannot find any such relationship.
(The fifth point in the list is aimed at any Monetarists who for some bizarre reason decided to read this article.)
Inflation is complicated, and there is no reason to expect that rents are going to move in the same way as college tuition, used automobiles, or imported jeans. To any extent we can model inflation, we need to decompose the aggregate (which was allegedly proved to be the wrong way to look at inflation, according some neoclassical economists).
The whole “unemployment needs to rise to reduce inflation” was a terrible take since it was a somewhat innumerate understanding of a “stylised fact” about recessions. Recessions tend to be associated with disinflation (rate of inflation dropping). As such, one strategy to control inflation is to throw the economy into recession whenever inflation is “too high.” (I am not saying that is a good strategy, but reading between the lines, that is the neoliberal strategy.) However, the causal implication is one way — a recession is (typically) sufficient for disinflation, but it is not necessary (as seen in the disinflation after the pandemic spike).
I am still plugging away at editing my inflation manuscript (interrupted by the CFL Labour Day Classic). Most of the work is tweaking existing text, and thus not publishable here. However, I added a missing section that should show up within a week or so.
If I were productive, I might be able to finish it off within a month or two. Based on past experience, a publishing date in January is more realistic.
I am working through my inflation book manuscript, and have not had much time to think about new articles. I added a subsection on producer price indices, and decided to go use that as my latest article here. I have added extra comments that is not in the manuscript since they are tentative.
Ben Bernanke and Olivier Blanchard recently published “What caused the US pandemic-era inflation?” The paper creates a basic model for inflation that is fit to data, and then uses it to attempt to decompose what drove the post-pandemic inflation.
The paper argues that the bulk of the inflation spike was mainly the result of “shocks” — energy, food, and their proxy for “supply shocks.” Once the shocks subsided, inflation calmed down. The labour market heated up (as proxied by the ratio of job openings to the number of unemployed) which raised inflation somewhat, but is supposedly more persistent and thus allegedly needs to be addressed.
One area of controversy that showed up after 2020 was about the role of “price gouging” in the overall rise in inflation. (This idea was satirically referred to as “greedflation.”) This has been an area of theoretical dispute between post-Keynesians and mainstream economists (as post-Keynesians argued in favour of a conflict theory of inflation), although it was not that a well-known dispute until after the pandemic. The obvious reason is that most people are not going to loudly argue about the sources of inflation when it was stuck near 2%.
Since I do not want this text to stray too far into theoretical disputes, I will just outline the ideas behind this debate.
Isabella M. Weber and Evan Wasner published the article “Sellers’ Inflation, Profits and Conflict: Why can Large Firms Hike Prices in an Emergency?” in 2023. The authors argue that the conventional story that inflation is always macroeconomic is incorrect, rather it can have microeconomic origins.
The abstract of the paper summarises how they saw the inflation process developing in this instance.
We review the longstanding literature on price-setting in concentrated markets and survey earnings calls and compile firm-level data to derive a three-stage heuristic of the inflationary process: (1) Rising prices in systemically significant upstream sectors due to commodity market dynamics or bottlenecks create windfall profits and provide an impulse for further price hikes. (2) To protect profit margins from rising costs, downstream sectors propagate, or in cases of temporary monopolies due to bottlenecks, amplify price pressures. (3) Labor responds by trying to fend off real wage declines in the conflict stage.
This fits within the wider literature of “conflict inflation” that characterises the post-Keynesian literature. The authors contrast this from a “macroeconomic” viewpoint, where inflation is the result of something like GDP growing above “potential GDP,” the unemployment rate being below the “The Non-Accelerating Inflation Rate of Unemployment” (NAIRU), or rapid “money” growth.
This does not correspond to “the inflation after the pandemic was the result of firms getting greedier than they were in 2019” (as some critics attempted to downplay the idea), rather it is a process that required concentration in “systemically significant upstream sectors.” There are always some firms raising prices to see whether they can pad profits, the issue is that there needs to be a mechanism for price hikes to propagate.
This idea fits in to the existing literature on “conflict inflation.” Conflict inflation is the standard post-Keynesian explanation for the inflation process. The mainstream view on conflict inflation is mixed. American neoclassical economists tend to reject the idea out of hand, while European mainstream economists were more sympathetic to the idea. The American stance tends to have a higher profile, presumably because they have stronger views on the topic.
For reasons that I will discuss below, it is going to be hard to come up with conclusive analytical evidence either way on this topic if we look at outcomes under the current economic structures. The differences between the views show up more in terms of offering different policy options to combat inflation.
Given that I am not in the policy advocacy business, nor do I want to discuss unresolvable theoretical disputes in this text, I will not pursue this angle. However, the policy implications of the concept are why it matters. If one is only interested in forecasting inflation in the current policy environment, it is somewhat hard to distinguish between this concept and others.
I believe that the mechanism described in the Weber and Wasner article was a factor behind the inflation spike (although I will note theoretical concerns later). The authors give examples of firms taking advantage of the situation to push through price hikes, and how they fit in with the story.
The advantages of this story versus conventional theories is that we had an inflation spike at the right time.
If one wants to blame “money printing” for inflation, why was there no inflation in Japan when they pioneered “Quantitative Easing,” or most of the major economies after 2008?
If one wants to blame “fiscal deficits,” we then can make pretty much the same response as in the previous point.
Trying to use the unemployment rate to explain inflation (e.g., the so-called “Non-accelerating inflation rate of unemployment (NAIRU)”) fails horribly. Inflation spiked when the unemployment rate was still quite high yet started to moderate even though the unemployment rate eventually hit low levels.
In summary, the supply chain disruptions were what distinguished the post-pandemic period from the rest of the post-1990 period, and that was the only period where inflation broke out. The supply chain disruptions were what gave “upstream firms” to ram through price hikes under this story.
At the time of writing, this line of argument is currently being debated, and I think the discussion will continue to shift. I have not seen an analysis that is truly conclusive one way or another.
The main difficulty is always going to be determining how much of the rise in inflation is due to rising profits. One method would be to try to estimate the effect company by company. The problem is that the ability to undertake such a survey is limited, and we need to question the reliability of things like statements on corporate earnings calls. Given that collusion to fix prices is illegal in some jurisdictions, corporate executives might shy away from stating that they did that publicly. Unless some form of survey was legally mandated to be submitted to national statistical agencies, it is going to be hard to connect anecdotal reports to the overall price index in a systematic fashion.
An alternative is that we could look at aggregate profits in the economy and attempt to assign contributions to overall price changes to the change in profits.
The previous figure shows “Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj)” as a percentage of national income from 2015-2022. There was an increase in the profit share after the disruptions in 2020, so one might try to argue that reflects companies padding profit margins.
The problem with this aggregate profit accounting story is the Kalecki/Levy Profit Equation. I discuss this equation in Section 4.2 of my book Recessions: Volume I. If we use a simplified version of the national accounts, the equation is:
Profits = (Net Investment) – (Household Savings) + (Dividend Payments) + (Government Fiscal Deficit) – (Net Imports).
(In the real world, the national accounts are more complicated, and there are more entries to the equation.) Importantly, this is not an opinion or theoretical model – it is an accounting identity. (An accounting identity is an equation that is true by definition – it just tells us how accounting entries add up when there are no errors in measuring the accounting entries.)
Although we could attempt to pin down the initial terms of the equation (net investment, housing savings, and dividends) by tying them to corporate pricing strategy within a model, the fiscal deficit and the trade deficit are determined by government policy and the state of the macroeconomy. Even if every firm in the economy wanted to raise its forecast profit margins, there is no guarantee that aggregate profits would rise.
An alternative way of viewing this concern is that one could create an economic model where prices and wages are constant. (For example, this describes many of the models I developed in my earlier book, An Introduction to SFC Models Using Python.) Even though profit margins on production are constant, profits in the model will still rise and fall due to other variables changing in the simulation.
Although the decomposition approach looks like the natural approach to test the theory, this is not necessarily the case. If the price hikes are being rammed through by “upstream” industries with pricing power, this results in downward pressure on the profits the “downstream” industries. Meanwhile, wages are also expected to rise.
If we move away from a “decomposition approach,” we face an additional concern: how much predictive value the concept has? It is one thing to have an explanation based on price hikes that have already happened and discussed in corporate earnings calls, it is another to have a forward-looking explanation that can be used to predict inflation. Why did we have no profit-driven inflation spikes from 1995-2020? Will we always need a disruption as large as the pandemic shutdown to have a repeat?
We can then run into variant idea, which was dubbed “excuseflation,” which was discussed in a Bloomberg Odd Lots episode by Tracy Alloway and Joe Weisenthal ( URL in references.). Excuseflation is the observation that it is a lot easier for a firm to find an excuse to raise prices when other prices are rising. If a lot of other prices are rising markedly, it is a lot easier to sneak in price hikes that raise profit margins.
Although I think that is a good description of the psychology, we run into a theoretical problem. Saying that people are observing other prices shoot up is very hard to distinguish from those people forecasting higher inflation. This means that this is very hard to distinguish from the mainstream concept of “inflation expectations” – at least if we take a broad definition of “inflation expectations.”
There was certainly a greater interest in the idea that price increases were the result of corporations trying to raise their profit margins after the pandemic disruptions. At the time of writing, it is still unclear whether it will shift how “mainstream” entities like central banks view inflation. My view is that it will be hard to find any data that can convincingly demonstrate an aggregate effect, although we certainly can find individual firms jacking up their prices and increasing their profitability.
The debate about the role of profit padding in inflation might result in a different perspective on how to control inflation, but that is outside the scope of this text.
Weber, Isabella M., and Evan Wasner. “Sellers’ inflation, profits and conflict: why can large firms hike prices in an emergency?.” Review of Keynesian Economics 11.2 (2023): 183-213. Working paper URL: https://scholarworks.umass.edu/econ_workingpaper/343/
“How ‘Excuseflation’ Is Keeping Prices – and Corporate Profits – High,” Bloomberg Odd Lots, Tracy Alloway and Joe Weisenthal. URL:https://www.bloomberg.com/news/articles/2023-03-09/how-excuseflation-is-keeping-prices-and-corporate-profits-high
The most introductory text discussing conflict inflation that I own is Macroeconomics by William Mitchell, L. Randall Wray, and Martin Watts.
The Cantillon Effect is the label applied to a process described in Richard Cantillon’s , «Essai sur la nature du commerce en général», published in 1755. (One English translation of the title is “An Essay on Economic Theory.”) The basic premise is that an initial inflow of money will raise prices as the original recipients of the money spend it, which will then raise other prices as the “new money” enters others’ hands.
I have started writing a section for my book on the “greedflation” debate: are corporations jacking up prices to pad profit margins? Since I wanted my book to mainly focus on basic facts about inflation that are true, and not unresolved theoretical debates, it is not entirely a great fit. I was planning on publishing my draft today, but I decided to hold back and explain why that is.
We will now conclude this chapter with some general comments on the relationship between inflation and the overall financial markets. What we see is that there are some areas of direct linkage between inflation (as measured by a consumer price index) and some financial assets, other assets have a more complex relationship. As a result, making generalisations is difficult – equity prices are not going to move the same way as the prices of cheesy snacks at your local convenience store.