- Gilets Jaunes and the age of commuter democracy Andrew Smith, Age of Revolutions
- Victor Klemperer’s dispatches from interwar Germany Peter Gordon, the Nation
- Harold Demsetz (1930-2019) and UCLA price theory Peter Boettke, Coordination Problem
- The rise and fall of the British nation Richard Davenport-Hines, Times Literary Supplement
A few days ago, I received goods news that the Canadian Journal of Economics had accepted my paper that constructed a consumer price index for Canada between 1688 and 1850 from homogeneous sources (the account books of religious congregations). I have to format the article to the guidelines of the journal and attach all my data and it will be good to go (I am planning on doing this over the weekend). In the meanwhile, I thought I would share the finalized price index so that others can see it.
First, we have the price index that focuses on the period from 1688 to 1850. Most indexes that exist for pre-1850 Canada (or Quebec since I assume that Quebec is representative of pre-1850 Canadian price trends) are short-term, include mostly agricultural goods and have no expenditures weights to create a basket. Now, my index is the first that uses the same type of sources continuously over such a long period and it is also the first to use a large array of non-agricultural goods. It also has a weights scheme to create a basket.
The issue of adding non-agricultural goods was especially important because there were important differences in the evolution of different types of goods. Agricultural goods, see next image, saw their nominal prices continually increase between the 17th and 19th centuries. However, most other prices – imported goods, domestically produced manufactured goods etc. – either fall or remain stable. These are very pronounced changes in relative prices. It shows that reliance on agricultural goods price index will overstate the amount of “deflating” needed to arrive at real wages or incomes. The image below shows the nominal price evolution of groupings of goods as described above.
And finally, the pièce de résistance! I link my own index to other existing post-1850 index so as to generate the evolution of prices in Canada since 1688. The figure below shows the evolution of the price index over … 328 years (I ended the series at 2015, but extra years forward can be added). In the years to come, I will probably try to extend this backwards as much as possible at least to 1665 (the first census in Canada) and will probably try to approach Statistics Canada to see if they would like to incorporate this contribution into their wide database of macroeconomic history of Canada.
In my previous post on this subject I argued that the critics of “anti price-gouging laws” are mistakenly assuming that is possible to satisfy demand at the pre-natural disaster price. That is, sadly of course, fiction. It it not our reality anymore and we are better accepting the new situation than blindly deny it. As many economists are explaining these days, to not let prices increase after a natural disaster does more harm than letting prices increase. This can easily be seen in a demand and supply graph.
Consider first just the lines in black. Those lines represent the pre natural disaster situation. What is considered “normal prices”. At price p0, a quantity q0 of a good is traded in the market (i.e. bottles of water.)
Now there is a shock. A hurricane hits this region and demand increases (shifts to the right). This is the demand line in color red. The red dotted line that extends to the right shows the size of the shortage (q2 – q1) at the “normal and fair” price.
Price gouging is an emotional loaded word, but it doesn’t have any specific economic meaning. How does “price gouging” show up in this graph? It is the increase in price from p0 to p1. This is the increase in price required to satisfy the higher demand and provide the extra number of goods (q1 – q0). No… supply is not horizontal.
What happens if price increases are banned? Then at the pre-crisis quantity (q0), consumers are willing to pay p2, a price even higher than price gouging. This means two things. First, a number of people in need will be unable to acquire the goods (the empty shelf problem). Second, that the actual total cost (to those who acquire the quantity q0) is p2, not p0. The difference between the price in the store and total cost falls into waiting in long lines, visiting a long number of stores, bribing producers (yes… with natural disaster price controls also lead to black markets), calling favors., etc. Any principles of microeconomic textbook has plenty of more examples under the price ceiling discussion.
There are three scenarios being discussed here.
- Quantity q0 at price p0
- Quantity q1 at price p1
- Quantity q0 at price p2
The natural disaster makes scenario 1 impossible. And it is not clear that scenario 3 is better for those in need than scenario 2. Less goods are provided at a higher total cost than in scenario 2.
One final remark. Note that in this analysis the natural disaster only affected demand. Of course, it is quite likely that supply would also be affected. The point, however, is to show that prices are not pushed up only by produces. As we can see in this case, it is consumers who are increasing the price and producers reacting to the new behavior of consumers.
I admit to being a happy man. While I am in general a smiling sort of fellow, I was delightfully giggling with joy upon hearing that another economic historian (and a fellow Canadian from the LSE to boot), Dave Donaldson, won the John Bates Clark medal. I dare say that it was about time. Nonetheless I think it is time to talk to economists about how to do economic history (and why more should do it). Basically, I argue that the necessities of the trade require a longer period of maturation and a considerable amount of hard work. Yet, once the economic historian arrives at maturity, he produces long-lasting research which (in the words of Douglass North) uses history to bring theory to life.
Economic History is the Application of all Fields of Economics
Economics is a deductive science through which axiomatic statements about human behavior are derived. For example, stating that the demand curve is downward-sloping is an axiomatic statement. No economist ever needed to measure quantities and prices to say that if the price increases, all else being equal, the quantity will drop. As such, economic theory needs to be internally consistent (i.e. not argue that higher prices mean both smaller and greater quantities of goods consumed all else being equal).
However, the application of these axiomatic statements depends largely on the question asked. For example, I am currently doing work on the 19th century Canadian institution of seigneurial tenure. In that work, I question the role that seigneurial tenure played in hindering economic development. In the existing literature, the general argument is that the seigneurs (i.e. the landlords) hindered development by taxing (as per their legal rights) a large share of net agricultural output. This prevented the accumulation of savings which – in times of imperfect capital markets – were needed to finance investments in capital-intensive agriculture. That literature invoked one corpus of axiomatic statements that relate to capital theory. For my part, I argue that the system – because of a series of monopoly rights – was actually a monopsony system through the landlords restrained their demand for labor on the non-farm labor market and depressed wages. My argument invokes the corpus of axioms related to industrial organization and monopsony theory. Both explanations are internally consistent (there are no self-contradictions). Yet, one must be more relevant to the question of whether or not the institution hindered growth and one must square better with the observed facts.
And there is economic history properly done. It tries to answer which theory is relevant to the question asked. The purpose of economic history is thus to find which theories matter the most.
Take the case, again, of asymetric information. The seminal work of Akerlof on the market for lemons made a consistent theory, but subsequent waves of research (notably my favorite here by Eric Bond) have showed that the stylized predictions of this theory rarely materialize. Why? Because the theory of signaling suggests that individuals will find ways to invest in a “signal” to solve the problem. These are two competing theories (signaling versus asymetric information) and one seems to win over the other. An economic historian tries to sort out what mattered to a particular event.
Now, take these last few paragraphs and drop the words “economic historians” and replace them by “economists”. I believe that no economist would disagree with the definition of the tasks of the economist that I offered. So why would an economic historian be different? Everything that has happened is history and everything question with regards to it must be answered through sifting for the theories that is relevant to the event studied (under the constraint that the theory be consistent). Every economist is an economic historian.
As such, the economic historian/economist must use advanced tools related to econometrics: synthetic controls, instrumental variables, proper identification strategies, vector auto-regressions, cointegration, variance analysis and everything you can think of. He needs to do so in order to answer the question he tries to answer. The only difference with the economic historian is that he looks further back in the past.
The problem with this systematic approach is the efforts needed by practitioners. There is a need to understand – intuitively – a wide body of literature on price theory, statistical theories and tools, accounting (for understanding national accounts) and political economy. This takes many years of training and I can take my case as an example. I force myself to read one scientific article that is outside my main fields of interest every week in order to create a mental repository of theoretical insights I can exploit. Since I entered university in 2006, I have been forcing myself to read theoretical books that were on the margin of my comfort zone. For example, University Economics by Allen and Alchian was one of my favorite discoveries as it introduced me to the UCLA approach to price theory. It changed my way of understanding firms and the decisions they made. Then reading some works on Keynesian theory (I will confess that I have never been able to finish the General Theory) which made me more respectful of some core insights of that body of literature. In the process of reading those, I created lists of theoretical key points like one would accumulate kitchen equipment.
This takes a lot of time, patience and modesty towards one’s accumulated stock of knowledge. But these theories never meant anything to me without any application to deeper questions. After all, debating about the theory of price stickiness without actually asking if it mattered is akin to debating with theologians about the gender of angels (I vote that they are angels and since these are fictitious, I don’t give a flying hoot’nanny). This is because I really buy in the claim made by Douglass North that theory is brought to life by history (and that history is explained by theory).
On the Practice of Economic History
So, how do we practice economic history? The first thing is to find questions that matter. The second is to invest time in collecting inputs for production.
While accumulating theoretical insights, I also made lists of historical questions that were still debated. Basically, I made lists of research questions since I was an undergraduate student (not kidding here) and I keep everything on the list until I have been satisfied by my answer and/or the subject has been convincingly resolved.
One of my criteria for selecting a question is that it must relate to an issue that is relevant to understanding why certain societies are where there are now. For example, I have been delving into the issue of the agricultural crisis in Canada during the early decades of the 19th century. Why? Because most historians attribute (wrongly in my opinion) a key role to this crisis in the creation of the Canadian confederation, the migration of the French-Canadians to the United States and the politics of Canada until today. Another debate that I have been involved in relates to the Quiet Revolution in Québec (see my book here) which is argued to be a watershed moment in the history of the province. According to many, it marked a breaking point when Quebec caught up dramatically with the rest of Canada (I disagreed and proposed that it actually slowed down a rapid convergence in the decade and a half that preceded it). I picked the question because the moment is central to all political narratives presently existing in Quebec and every politician ushers the words “Quiet Revolution” when given the chance.
In both cases, they mattered to understanding what Canada was and what it has become. I used theory to sort out what mattered and what did not matter. As such, I used theory to explain history and in the process I brought theory to life in a way that was relevant to readers (I hope). The key point is to use theory and history together to bring both to life! That is the craft of the economic historian.
The other difficulty (on top of selecting questions and understanding theories that may be relevant) for the economic historian is the time-consuming nature of data collection. Economic historians are basically monks (and in my case, I have both the shape and the haircut of friar Tuck) who patiently collect and assemble new data for research. This is a high fixed cost of entering in the trade. In my case, I spent two years in a religious congregation (literally with religious officials) collecting prices, wages, piece rates, farm data to create a wide empirical portrait of the Canadian economy. This was a long and arduous process.
However, thanks to the lists of questions I had assembled by reading theory and history, I saw the many steps of research I could generate by assembling data. Armed with some knowledge of what I could do, the data I collected told me of other questions that I could assemble. Once I had finish my data collection (18 months), I had assembled a roadmap of twenty-something papers in order to answer a wide array of questions on Canadian economic history: was there an agricultural crisis; were French-Canadians the inefficient farmers they were portrayed to be; why did the British tolerate catholic and French institutions when they conquered French Canada; did seigneurial tenure explain the poverty of French Canada; did the conquest of Canada matter to future growth; what was the role of free banking in stimulating growth in Canada etc.
It is necessary for the economic historian to collect a ton of data and assemble a large base of theoretical knowledge to guide the data towards relevant questions. For those reasons, the economic historian takes a longer time to mature. It simply takes more time. Yet, once the maturation is over (I feel that mine is far from being over to be honest), you get scholars like Joel Mokyr, Deirdre McCloskey, Robert Fogel, Douglass North, Barry Weingast, Sheilagh Ogilvie and Ronald Coase (yes, I consider Coase to be an economic historian but that is for another post) who are able to produce on a wide-ranging set of topics with great depth and understanding.
The craft of the economic historian is one that requires a long period of apprenticeship (there is an inside joke here, sorry about that). It requires heavy investment in theoretical understanding beyond the main field of interest that must be complemented with a diligent accumulation of potential research questions to guide the efforts at data collection. Yet, in the end, it generates research that is likely to resonate with the wider public and impact our understanding of theory. History brings theory to life indeed!
“Unspent dollars means reduced sales, and as sales decline, profits drop, layoffs increase, and the total social income decreases, making less money available for consumption. Hoarding induces more hoarding as the economy sinks into a downward spiral.” (Smith, 2009)
That’s a lot of nonsense in just two sentences. (Note this is Smith’s paraphrase of the anti-hoarding argument, which he ably disputes.)
First, there is no distinction between “spent” and “unspent” dollars. Money jumps instantly from one pocket to another whenever it is used in a transaction. All money is “idle” between jumps. This could refer to the demand to hold money which is the inverse of the velocity of money. We hold money for convenience, safety, and occasionally as a hedge against deflation.
Second, decreased velocity means price deflation, other things being equal, and if a fall in velocity happens suddenly and unexpectedly, it can be a temporary boon to buyers and a detriment to sellers. But the idea of a deflationary spiral feeding on itself is silly, if only because we all have to eat. Low prices are the cure for low prices, as bargain-hunters move in and prices stabilize.
Then there’s this “social income” phrase. Real social income is not enhanced by faster spending. It is enhanced by greater productivity which depends on private saving, which in turn depends largely on property-friendly institutions. We cannot spend our way to prosperity.
I’ll also comment on Kaminska’s claim that bitcoins “do not benefit the economy” because they do not bear interest. Along with currency and (in their time) gold and silver coins, bitcoins are what economists call “outside money” meaning they are an asset that is no one’s liability. Checking account balances are a form of “inside money” because they are at once an asset of the account holder and a liability of the bank. When outside money is deposited in a fractional-reserve bank where it becomes inside money, some is kept in reserve and some is loaned out. This apparently what is meant by “benefit to the economy” but in fact it’s a benefit to the bank which can earn profits on the new loans and to the borrower, if all goes well. It’s a detriment to the rest of us because there is an increase in the money supply which causes price inflation.
There is nothing anti-social about holding outside money. Some of us see marginal benefits in holding outside money (security, convenience) that exceed the cost in foregone interest. So what?
My own two cents on this (get it?) is merely that Dr Gibson needs to spend more time at NOL fixing the mistakes of financial journalists and keeping his fellow economists honest. (Notereaders and Notewriters, holla at me and Warren in the ‘comments’ threads if you agree!)
Similar to Brandon I’ve began playing around with new statistical packages. Like many libertarian scholars I have my skepticism about the limits of what we can learn from number crunching. I think there is a place for statistical analysis in the social sciences, but it is definitely meant to be a tool, not an ends to itself, and should be complemented with additional methods.
Recently I’ve begun trying to find a Geographical Information Systems (GIS). I had initially intended to buy a copy of ArcGIS, one of the dominant GIS packages, until I looked at their pricing plans. A single license for the basic version costs $1,500 USD. I’m sad to say this price tag is not abnormal. STATA, one of the larger statistical packages, sells an annual licence for its bare bones version at $125 USD. SAS has its pro version going for $9,000 USD.
What is abnormal is that several freeware packages exist that provide comparable services. Are you an undergraduate student taking a class on univariate regression analysis? Download Gretl. It has a menu based system that is relatively easy for even the newest of users to play around with. If you’re looking to challenge yourself opt instead for R.
Likewise, for those who like me are on a budget, there exists several freeware alternatives for GIS systems such as GRASS and QGIS. I’m still learning GIS so I can’t comment on either package, but I will be sure to provide reviews once I’m comfortable with them.
If several freeware alternatives exist, why do retail versions remain dominant in the industry?
Part of the answer is that corporations and universities value the customer help hotline if their software starts to malfunction. Poor graduate students don’t have much money, but tend to have a surplus of free time to use trying to figure out why their software isn’t working. Corporations have the opposite constraints, they have infinitely more money than graduate students but have much stricter time constraints.
Surely that can’t explain it all though, can it? If what you are purchasing with retail packages is the customer hotline, why haven’t a group of entrepreneurial (and hungry) grad students set up a business where they provide dedicated IT support for freeware? Several attempts have been made by Linux enthusiasts to provide such services for corporations looking to replace their Microsoft OS systems, so the idea has surely been thought of before.
Another possible answer is that what these retail packages are selling is their community. STATA may not be so technically superior to Gretl, but the former’s community is larger than the latter. If you have a problem with Gretl you can’t easily find another user to help out outside of a few niche forums. Meanwhile you are sure to find a STATA compatriot just by walking down a social science college’s halls. I am not really convinced by this idea though. There is a value to joining an existing community, but in the long run people do move across networks. Consider Myspace, which less than a decade ago was the social network, until it was defeated by another social network. How much longer will STATA and ArcGIS last before its user base migrate to R and GRASS?
What do you all think? What other reasons might explain why pricey retail statistical packages remain dominant over comparable freeware alternatives?
In case you haven’t noticed, the price of oil has dropped dramatically and has not rebounded as yet. As I write, the price of the most common form of crude oil is under $54 per barrel, about half of what it was in mid-2014. What’s going on?
Several factors contributed to the fall. One was increased U.S. production, much of it shale oil. Also, U.S. consumption has not been rising apace with GDP in part because of higher fuel efficiency. Demand in Europe and Japan is muted due to low growth or recession.
Those things did not happen suddenly, however, so the drop would appear to be overdone. Large producers, who have a lot of pricing power, would normally cut production in this circumstance. (Pricing power means a change in their production has a noticeable effect on the world price.) The Saudis have considerable pricing power and their production decisions are controlled by their government. Why have they not cut production? I believe they are engaging in predatory pricing.
Predatory pricing is illegal in the U.S. and elsewhere, under anti-trust law. Predatory pricing occurs when a supplier cuts his prices for the purpose of bankrupting a competitor, or at least driving the competitor out of the market. The predator is willing to suffer losses or reduced profits temporarily, while holding the prices low. Once the competitor is gone, the predator’s pricing power will have increased enough that he can raise prices a lot and make up for losses suffered during the period of predation. Predatory pricing is definitely possible in free markets but is very risky for several reasons: (1) the predator can’t be sure how long it will take to ruin his competitor, (2) he can’t be sure how long he can maintain low prices without sustaining ruinous losses or perhaps face a shareholder rebellion, (3) it’s possible the competitor, or someone who has bought his assets in bankruptcy, will come back to life and start competing as before. For these reasons (and others, such as the difficulty facing regulators who are supposed to distinguish predatory motives from “innocent” business strategy), I believe there is no reason to outlaw predatory pricing.
The situation is a little different in the international oil market because the Saudis and many other major players are government controlled. They are not constrained (much) by the market forces outlined above. They are not accountable to shareholders and are only vaguely responsible to the population of Saudi Arabia. They have substantial latitude to pursue political motives even if their profits suffer. And anti-trust law does not operate across national borders.
What might the Saudis want to accomplish politically? They hate Russia and Iran, both of which rely heavily on oil exports. They don’t hate the U.S., at least not openly, but they surely wouldn’t mind sticking it to U.S. and Canadian shale oil producers. Those producers are largely market-driven and thus have limited ability to withstand predatory pricing. The Saudis could indeed drive smaller firms out of the market, and also less profitable operations of larger firms.
That might not be such a bad thing. There has been a huge land rush into shale oil and fracking. In any such boom, whether in energy, mining, or computers, many small firms fall by the wayside. If the Saudis ruin some marginal firms or projects, that’s not such a bad thing.
We little guys are sitting pretty. We’re paying a lot less for gasoline. If we hold shares of the major oil firms we’re probably OK, as their share prices have held up and their dividends look solid. The same is true of the pipeline operators. Only if we hold shares of marginal energy firms or oilfield service companies are we in any trouble.
So – go for it, Saudis! Stick it to the evil governments of Russia and Iran and help us clean out some of our marginal energy operations.