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Cannabis Laffer Curve Expanded:
The Netherlands Sparked North American Interest

In an earlier post, we examined the recreational pot tax structure.  Using US-only data, we discovered that at its frontier, a Laffer Curve formed that described the maximum amount of tax revenues possible given specific tax rates.

Here we entertain other authorities taxing legal recreational pot.  Added to the blue points forming a limit is another describing the tax rate and revenue per user for The Netherlands (NL) in 2008 (adjusted for inflation).  Through these blue points, the Laffer Curve explains 90% of their variation and is highly negative (power exponent -1.61).

Also considered now but not part of the Laffer Curve is the recent experience of British Columbia (BL 2019).  Observe it registered minuscule tax revenues.

At least 3 factors influence cannabis tax receipts: 1) Ease of legal access: BC, OR, and CA lag far behind their better-organized counterparts in making legal recreational marijuana sufficiently available.  2) Tax rate: From 15.3% (NV 2019) to 108% (WA 2014), revenues go up as tax percentages go down.  3) The proximity of lower-cost options: some would-be CA or CA tourist receipts or go to NV or black markets.

#laffercurve #market #marketanalysis #price #taxpolicy #demand #tax

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NFL Wideout Valuation: Go Faster

In 1968, Rocky Bleier joined the Pittsburg Steelers.  After the season, once drafted, he volunteered for duty in Vietnam.

When he came #price to the team camp in 1972, he posted a 4.6-second 40-yard dash.

With part of his right foot blown off.

His previous best was 4.8.

What’s the value of added speed for veterans?  If we remove the rookie contracts and draft halo effects by looking at pros in the league for six or more years (thanks, Jem Anderson!), we can find out.  A shows us the total compensation for NFL wideouts goes up with receptions per game.  At the same time, their value falls dramatically with age.  Speed plays a role too. A 28-year old receiver with 4 catches a game running a 4.65 40-yard dash is worth about $6 million per year (note the equation forming surfaces A and B has P-values of 6.43E-07, 0.41%, and 3.6% for catches/game, age, and 40-yard times, in that order, and 2.32E-06 for the entire equation).

In B, we take another 28-year old with 4 receptions/game, but this one runs the 40-yard dash a quarter second quicker.  The extra speed adds another 2/3 to his compensation, bringing it to $10 million.

It’s hard to improve speed.  But if you can do it in the NFL, it pays off.

#value #valueproposition #generalmanager #worth

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NFL Wideout Valuation

If you’re into the game, you probably have a rough idea about how the National Football League assigns values to its players. A little analysis provides unexpected insights.

Each dot in A and B denotes one of 106 NFL wide receivers in 2019. A’s plane shows the value the league assigns to them. It’s a function of their league years, receptions per game, and draft round (P-values of 7.70E-17, 5.84E-08, 0.02%, respectively, and 6.61E-25 for the entire equation, with an adjusted R^2 of 66.7%). Here, we’ve set the round to 1, years to 4, and receptions per game to 3.04. For those valued features, the NFL awards a wideout with $5 million/year.

B shows us how others can get the same. If we keep league years at 4, we find that if we increase the receptions to 6.09, a 3rd-round wideout (note lower plane) can get as much as a 1st-rounder.

That’s twice the receptions for the same salary.

Knowing this informs decisions. If too-high valuations for 1st-rounders come from long contracts too often, perhaps GMs should seek shorter terms. If a 3rd-rounder receives an extended period offer at a low rate but knows he can perform, maybe he should negotiate for bonuses for his excellent work.

#nfl #nfldraft2020 #players #playervaluation #valuation #value #generalmanager

Laffer Curve Quantified: Pot Taxes Get Too High

The Laffer Curve is the relationship between tax rates and revenues.  For income, taxes of 0% or 100% produce no tax revenue.  Maximum tax receipts lie in-between.

The study of this phenomenon has mainly been theoretical.

The recent rush of states legalizing recreational marijuana gives us a real-world example.

In 2014, Colorado and Washington legalized recreational pot.  Other states followed suit, all with different tax rates.  If we exclude the results for Oregon and California in 2019 (in red), the remaining six blue points form most of the Laffer curve for cannabis.  This blue power curve is highly negative (exponent -1.55) and significant (P-value 1.96E-03).  It explains why Nevada, in 2019, made over 30 times as much per cannabis user as did Washington State in 2014.

In 2019, California, with nearly 13 times the population of its neighbor Nevada, made barely half of the receipts of The Silver State.  California struggles mightily with the cannabis black market because of its tax policy.  There’s a lesson here: Never turn a market analysis problem into a legal one.  If someone blows smoke your way arguing for high marijuana taxes, don’t inhale.

#Laffercurve #markets #marketanalysis #cannabisnews #cannabistax #taxpolicy

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COVID-19: Wealth, Density, Population, and Latitude

In the last post, we discovered an Upper Infection Limit for COVID-19.  Its cases positively correlate to density (as expected) and per capita GDP (not expected).  After Mike McRae wrote that “COVID-19 Deaths Are Being Linked to Vitamin D Deficiency (Health, May 1, 2020),”  I decided to dig deeper.

I found COVID-19 has a Lower Infection Limit at work, too.  Shown in white below, the line describing this threshold has an adjusted R^2 of 93.5% and a P-value of 3.05E-06, reflecting that it did not come about by chance.  The difference in the countries that form each line is just as significant.

Excepting Qatar and the United States, all of the countries along the upper curve are European, and their southernmost extent is 37°55′ N (the southern tip of Italy).  The nations forming the Lower Infection Limit are Asian or African, and, if we remove India and China, their northernmost point is 28°32’N (Myanmar), with most of their landmasses in the tropics.

Given the relative success of the tropical countries, should we increase sun exposure in northern climes?  How does sun angle to the ground regulate Vitamin D uptake and Coronavirus inflection rates?

#COVID #COVID19 #population #infection #VITAMIND

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COVID-19 Analysis in 4D

Many variables are at work in the COVID-19 pandemic.  Analyses in 4 dimensions help visualize them.  In markets, such structures use prices as objective functions.  As the virus seeks to replicate, its goal is to infect hosts.  We see each infection as a case.

At right, we plot countries’ populations against their COVID-19 cases on April 28, 2020.  Each dot signifies one of the 163 nations in the study.  Unchecked, only the size of the global community caps the number of cases.  However, we observe a yellow line marking the disease’s Infection Limit on that date.  That line is well-correlated (98.6% R^2); there is little chance it came about accidentally (P-value of 8.21E-10).  Countries on or close to that frontier are worse off than those far away from it.

The green side plane represents an equation derived from the population (set to 720,000,000), density, and GDP per capita (P-values in turn of 3.13E-35, 0.68%, and 5.90E-35).  While we would expect infection rates to go up with density and population, its strong relationship to GDP is unexpected.  Wealthier nations have more resources to fight such outbreaks, but it appears their travel patterns more than offset that.

#covid19 #covid19research #covid19analytics

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Walk This Way – It Could Be More Lucrative

How do businesses’ pay to give workers a short stroll to amenities?  Using open-source data, we find companies buy easy access to nearby banks, stores, and cafes as they pay for office space and zip codes.

In A, we see LA commercial real estate prices rise with square footage and nearby household income (P-values 3.82E-16 and 0.01%, respectively), as shown by the surface.  Included in the calculation of that log-linear plane is “Walk Score,” which “measures the walkability of any address (www.walkscore.com, no affiliation with me).”

B shows the Walk Scores of 60 properties versus their prices.  Walk Score is a statistically significant (P-value 0.69%) contributor to Value (as sustainable prices).  The overall equation uses square footage, household income, and Walk Score.  It has an adjusted R^2 of 71.8%, implying there’s more work to do.

Figures C and D reveal that in Feb 2020 LA, doubling the Walk Score more than proportionally lifted the sustainable price.  Firms wishing to put up a new facility need to know this.  If the added Value of a new building exceeds its added cost, it may be worthwhile to set it up in high walkability areas.

Is NYC like LA? Look at the next post.

#price #marketanalysis #marketintelligence #realestate #target

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Physical and Market Targets

Aiming at and missing is much the same for battles and marketplaces.  We account for inaccuracies in the same way.

In A, a pilot sits in a Caudron G.3, an Allied surveillance plane in WWI. Note the fuselage aft of his seat.  Scenario B recounts a different G.3 pilot on an observation sortie, climbing out during a massive artillery battle.  An unseen friendly battery aims at a bridge, 1.  Their shell comes up short (2), wide (3), and high, as it strikes the plane (4).  As we move from 1 to 4, those lines trace out a Ballistic Error Tetrahedron, a miss across three dimensions (latitude, longitude, and altitude).  Figure C reveals the mission’s surviving American Expeditionary Force officer, my grandfather.  The round shot off part of the plane behind him.

We see the same construct in D. Here, a manufacturer sets a price for a business jet, 1.  However, if the airframer loses passenger capacity, the plane’s value falls to 2.  If it drops more features, as maximum speed and range, its sustainable price shifts to 3, then 4, respectively; this, too, is a 3-dimensional error, one we call a Value Error Tetrahedron.  Combined with the last post’s analysis, it reveals a 4D miscue.

#price #target #marketanalysis #marketintelligence

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Missing Price Targets

Businesses frequently set price goals. What does it mean not to hit them?

In A, we predict 1, the price of a barrel of oil. When the forecast date arises, the actual price, 2, varies, resulting in a one-dimension Error Line. We know by how much we missed, but nothing else.

B shows us what it means to be off-target in archery. If we aim at 1 and land on 2, we create an Error Triangle. That’s a two-dimensional error, in elevation (up and down) and azimuth (left to right).

In C, where every blue diamond stands for a business jet, we propose a new one. We set our target quantity and price, as 1, on the Demand Frontier, the line through the market’s outermost quantity-price points, in yellow. If we can’t put in enough features to support that price, we’d make a plane fetching less money, as 2. Moving from 1 to 2, we make a Demand Error Triangle.

But, in D, we find as prices fall, we might be able to sell more models. Analysts should find the Demand Frontier Slope to ascertain the amount of revenue available at market limits. That will be the areas under the curves, the green rectangle for 1, the orange one for 2.

What does it mean to miss price targets in Value Space? Find out in my next post.

#prices #demand #demandplanning #demandforecasting

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Real Demand Curves In Action

The rock star Meatloaf tells us that “Two out of three ain’t bad.”

But, when it comes to, say, selling your new supersonic jet, it can be.

One can adequately estimate a product’s Cost and Value (as a sustainable price for the first business jet to go over 1,000 miles per hour) only run afoul of its market’s Demand Frontier.

Below, we find Aerion offers a credible development Cost target for its supersonic AS2 (see A), and offline there is evidence its $120 million Price works for the market. Their problem lies with Demand. They forecast a market of 500 models, with 300 in a decade. But in the ten years studied in B, their forecast exceeded the limit of the Upper Demand Frontier (P-Value 4.91E-04). Five years later, in C, the Demand Frontier (P-Value 5.39E-05) shifted only slightly. As of January 2020, the company still only has the 20 orders they received in 2015. Currently, its chances of selling 300 units at $120 million in a decade are less than 25%.

COVID-19 or other forces may increase business jet demand, moving the Demand Frontier where Aerion would like it to be.

Failing that, the company likely got Cost and Price right, but missed Demand.

In business, two out of three is bad.

#demand #demandforecasting #marketanalysis #prices