Which Came First?
An article written years ago, Why Supply and Demand Are Hard to Measure, illustrates some of what I see continuing in our present time, where our market is simply referred to as, “weird times.” In the article cited above, the author points out that when trying to create a relationship between data (in this case wealth or poverty as they correlate to broadband usage) and the resulting supply or demand curve, the output can be fraught with problems. On this point, I’ll quote from my most recent economics text,
Like quantity demanded, the quantity supplied in a market typically responds to many influences other than price…a change in the price of the good causes a movement along a fixed supply curve. Price is not the only influence on quantity supplied, however. If any of these other influences change, the entire supply curve shifts…any rise in quantity supplied attributable to an influence other than price, however, will shift the entire supply curve outward to the right (Baumol & Blinder, 2010).
By this very definition, the implication is that a measurement along a supply curve is rarely, if ever static.
Difficulty in Forecasting
This principal is closely related to similar patterns in the basic study of finance, where we observe that formulas might help build a model for explanation of a market and forecasting. But with the many complexities of the human element, these predictions can be proved inaccurate at best. Or in the case of this article, countries, wealth and poverty differ tremendously, causing difficulty measuring the supply curve,
So does a graph of broadband prices and quantities in different countries tell us about the supply curve or the demand curve? Unfortunately, it’s a mishmash…if both curves were the same in every country, broadband prices and use would be the same in every country. However that’s not what we observe. Prices and quantities differ across countries. But is this because their supply curves differ or their demand curves differ? (Wolfers, 2009).
I think this is a material point to understanding this principal in any industry and helps explain the difficulties in getting our hands around our present time: how do we accurately create an apples to apples comparison when attempting correlation between two data sets? What’s more, how do we accurately create this model when we have hard data on one side, such as how many users are on broadband (or a percentage, etc.), and data that is not so easy to define such as wealth? How do you accurately articulate need? By demand only? These complexities are not so easily defined, especially in a short article attempting to answer a complex question (an inherent problem in the world of blogs). Wolfers sums it up as follows, “when you plot real-world price and quantity data…you learn a combination of the slope of both demand and supply, and the extent to which variation is driven by these two forces.”
The Principle Illustrated in How I Get to Work
I think this principal is underscored in the article, Chevy Volt and Nissan Leaf Sales Expected to Go Up in 2013 citing the Chevy Volt still hovering at the dizzy height of around $40,000. There are many drivers beyond price that have direct implications on the purchase of an all-electric vehicle. Price probably is the first and greatest barrier to entry, but there are others. I personally have wanted an EV for years, and have even looked into DIY kits to convert a vehicle (as if I had the ability to do this). My main motivation is the lack a real variance in fuel prices among establishments and how much I would love to bypass the whole process. In the past, distance has prohibited this possibility due to limitations of the EV’s range, even if I could afford one. I would guess that many others are in the same situation. Right now I only commute fifteen miles to work (through a series of vineyards), and rarely need to go beyond a 3-mile distance from our home during the week. The range of an all-electric vehicle would be more than adequate. So what do I do? I take the bus. But putting that aside, another factor has been the indirect prohibition of the electric vehicle. I do not lean toward conspiracies but the idea of an EV is not new,
The fundamental reasons why the electric car has not attained the popularity it deserves are (1) The failure of the manufacturers to properly educate the general public regarding the wonderful utility of the electric; (2) The failure of [power companies] to make it easy to own and operate the electric by an adequate distribution of charging and boosting stations. The early electrics of limited speed, range and utility produced popular impressions which still exist (Electric World, 1916).
Yes, that was written ninety-seven years ago! So why has supply been truncated almost out of existence for nearly 100 years? There are probably many answers to this question, but it illustrates the difficulty in measuring supply and demand curves. It also demonstrates the complexity for the financial analyst or anyone looking to create meaningful forecasts, such as where interest rates are going to be next year.
References:
(1916). Electric Vehicle Sessions. Electric World. http://books.google.com/books?id=SKkvAAAAYAAJ&pg=PA1236#v=onepage&q&f=false
Baumol, W. & Blinder, A. (2010). Economics: Principles & Policy (11th ed.). Mason, OH: South-Western Cengage Learning.
Hunter, N. (2013). Chevy Volt and Nissan Leaf Sales Expected to Go Up in 2013. http://eaglesrant.com/chevy-volt-and-nissan-leaf-sales-expected-to-go-up-in-2013/4138/nathan-hunter
Wolfers, J. (2009). Why Supply and Demand Are Hard to Measure. The New York Times: The Opinion Pages. Freakonomics. http://freakonomics.blogs.nytimes.com/2009/05/27/why-supply-and-demand-are-hard-to-measure/?scp=20&sq=supply&st=Search