pot project - final

2016

Measuring the Health of the Retail Marijuana Market

BU 5210 – Professor Chen Wu

Marc ROPER


THE DEBATE: KEY LITERATURE REVIEW

There is certainly much literature out there which strongly debates which public policy is

more favorable between marijuana prohibition and legalization. Yet with all the supporters and

nay-sayers, the simple truth is that American society doesn’t know with actual confidence the

potential economic benefits or catastrophe that would be if recreational marijuana were to be

legalized. What society does know is how society would function if its recreational use were

illegal; since this has been the stance on the drug since its use became popular. The following

section is simply an informative realization of the main arguments regarding the subject of

legalizing the drug.

Fundamental economics is rooted deeply in the simple evaluations of opportunity costs;

that is to say forgoing one set of resources and outcomes due to the choice to pursue a set of

alternative resources and subsequent outcomes. Thus, it must be reiterated that whatever should

be suggested as either pro or con-marijuana legalization implies its own set of opportunity costs

as well. For instance, as has been the case with prohibitive policy towards recreational

marijuana use, the decision to uphold this policy is forgoing any possible benefits from a policy

that would legalize such a drug. Of course the common retort would be ‘but what benefits exist

from the legalization of an addictive, gateway drug?’. Duly noted. And at first glance to the

naïve mind, it would be easy to critique policy proposals considering legal cannabis. Yet, resist

the urge to cement yourself in a hasty decision on your stance with the matter. For uncovering

the opportunity costs within may lead to tell a different story (or not).

Take into consideration the health and safety of the general public. For that is the role of

the federal government, to serve and protect the people of its nation. This initiative to protect the

citizens has been put on the forefront since 1982 following President Nixon’s declaration of the

war on drugs. It’s common perception then that prohibiting the use of recreational pot shields

the public from debilitating drugs. Still, all of this energy spent of prohibiting the use and access

to the drug, let us look into the opportunity cost surrounding the health and wellbeing of citizens.

(Shanahan & Ritter, 2014) Recognize that their largest reservations from a status quo versus pro-

weed policy, is the effect either policy has on the wellbeing, healthcare expenditure and

educational attainment of individuals. From a different perspective, an Alaskan report for Boreal

Economic Analysis & Research investigating the economic implications of marijuana

1


legalization, (Bates, 2004) notes that a total of 1233 arrests for marijuana offenses were made

between 1997 and 2001. However, of these, merely 147 for the sale or manufacturing of the

drug; while all 1086 other arrests were for possession. Signifying 88% of all marijuana arrests in

Alaska during that time period specific to simply possessing the drug. Furthermore, (Bates,

2004) revealed that the state of Alaska spent $64 million (2001 USD) on policing expenditures,

at least $2.4 million which can be directly linked to only marijuana specific policing. The same

report further details that of drug arrests (1997-2001), weed arrests accounted for 66.1% and

45.2% within Alaska and the entire USA, respectively; while of all drug arrests for reason of

possession, marijuana represented 73.4% in Alaska and 49.6% nationally.

The point of emphasis here is the staggering number of man hours, monetary

commitments and subsequent incarcerations which could be avoided (perhaps not all but most) if

cannabis were to be legalized. For one, the policing expenses would disappear. Perhaps not

completely, but a significant cut could be made to the active monitoring of marijuana operations

and more actively concentrated towards society. The individual officers could concentrate their

time elsewhere as well; for instance, towards the constant threat of gun violence, or border

patrolling. To put this idea of man hours into perspective, take the study of (Geller & Fagan,

2010) which reveals more thorough investigations into street policing in New York City. (Geller

& Fagan, 2010) mostly noted the aggressive “stop, question and frisk tactics” which were

predominantly aimed at reclaiming “the streets by systematically and aggressively enforcing

laws against low-level social disorders” (Geller & Fagan 2010, 594). More specifically, (Geller

& Fagan, 2010) findings indicate an increase in marijuana arrests form 2004 through 2008 of

nearly ten times its rate from the mid- 1990’s. Again, the legalization of cannabis may not rid

the city of all these arrests, but it would certainly diminish the amount of possession arrests,

while freeing up the seemingly senseless amount man hours police forces are committing to

marijuana monitoring.

Moreover, society would have fewer individuals in correctional facilities. The economic

perspective of losing members of society to such a crime sacrifices the wellbeing of the potential

aggregate economic output of the nation (Bates, 2004). If one were to think about

unemployment rates, the argument could be made that increasing the number of arrests, hence

the number of inmates in prison, could be the same as increasing the unemployment rates in the

2


country; as while physically able, they would not be significantly contributing to the labor force

and therefor hindering potential Gross Domestic Product output.

(Clark, May 2003) Acknowledges that prohibition (of all drugs) further emphasizes the

existence and growth of the black market for each respective good. (Bates, 2004) in fact, proves

that prohibition policy in Alaska has been ineffective in reducing the use of marijuana over the

years throughout all age category; only making the continued use in prohibition years all-the-

more risky to the citizens. Both (Bates, 2004) & (Clark, May 2003) explore the implications of

the black market and both conclude that a legalized and properly regulated marijuana market

would minimize and mostly abolish the black market for the drug. Why would riding society of

a cannabis black market be beneficial? For one, making marijuana a legal and public good

would allow government to regulate what is in the drug. This becomes an issue of protecting the

people once again as the question is posed: Should the government allow the black markets to

exist while keeping the drug illegal and running the risk of putting users in danger of not

knowing what they are using consists of? Or is it morally correct to legalize pot, knowing full

well that the government can regulate industry inputs during production to make the use of it

safer to marijuana consumers (Clark, May 2003) & (Bates, 2004)? Thus maintaining the

prohibitive policy for marijuana could arguably be keeping the black market open and thriving,

while putting individual consumers in serious risk.

Another largely debated topic when it comes to the legalization of pot is the potential for

government tax revenue in reference to the sales of recreational use. (Clements, Lan, & Zhoa,

2010) Simply outline the potential for tax revenue seen below. In figure 1, point A represents

the market demand when the use is

still illegal, and the corresponding price

in the black market. Point B signifies

the market demand while legalizing the

drug with no tax. The reason price

drops so low is due to the lack of risk

premium; a concept which

acknowledges the higher price in the

black market because of the risk black

3Figure 1 - Clements, Lan & Zhoa 2010


market suppliers must go through to get their product to consumers. If legalized and not tax,

there becomes no risk for producers, merely production costs to cover. Finally point C

highlights the market demand equilibrium with legal cannabis that is tax by the government and

the shaded area allows us visually to realize the tax revenue that would be generated (Clements,

Lan, & Zhoa, 2010). Such a proposition can be very enticing from an economic perspective. It

presents the theory of essentially unlocking a brand new, legal, and taxable market that has

untapped potential for profits; both from a producer and tax revenue standpoint. (Shanahan &

Ritter, 2014) Further highlight the potential financial benefits of an untapped market with net

government revenue of $659.4 million USD if pot were regulated. This is in comparison to

generated revenues of $318.8 million USD (legal & no taxation) and $362.7 million USD (illegal

status quo benefits). As is the case for (Shanahan & Ritter, 2014), most literature that attempts to

evaluate cannabis tax revenue benefits typically assume similar taxation levels to its

complimentary good - tobacco.

Of course, the theory sounds great. Yet actually quantifying such prospective data

becomes the challenge before committing to such a large scale policy proposition. As seen

above, without taxation, the respective price level would drop significantly. If the sale of

cannabis were not to be taxed, the price would certainly drop much lower than current prices

(because of the avoidance of a risk premium within a legal market), but this could be

substantially more impactful on substitute goods within the market place. More simply put, the

burden is put on the market for products such as tobacco, alcohol and other drugs. By allowing

price to drop too low for an untaxed, legal marijuana policy, governments run the risk of losing

these other legal markets of goods all together by making cannabis too readily available at a

reduced price.

This last point highlights a need then to identify different elasticities relative to marijuana

demand, as well as the nature of the good’s complimentary and substitute goods. For knowing

these pieces of information, an analysis could more accurately be conducted to forecast (but not

limited to) expected performance of sales relative to income (price elasticity), market demand

(demand elasticity), complimentary and substitute goods (cross-price elasticities). In their study

estimating the demand market for retail marijuana, (Clements, Lan, & Zhoa, 2010) determined

price elasticities of 1.2, 0.4 and 1.0 for marijuana, tobacco and alcohol, respectively.

4


Furthermore they were able to deduce that marijuana and tobacco were in fact compliments,

while pot and alcohol were substitute goods; these findings were backed up by (Cameron &

Williams 2001), (Zhoa & Harris 2004) and (Barry, Hiilamo, & Glantz, 2014). The problem that

persists, which admittedly applies to all marijuana data critique, is that the drug is still in fact

mostly illegal. As a result, data on its use, market demand and price is subject to a larger room

for error or inaccuracies. Not to mention the subject for varying market demand functions within

each country (market). Which essentially means forecasting a prospective marijuana market

relies heavily on assumptions; assumptions that cannot be guaranteed in real life policy making.

This fact further complicates and muddies the water of the decision process to legalize retail

marijuana. All of which (Clements, Lan, & Zhoa, 2010) also identify in their study.

Circling back to the point on price determination and regulation; it was determined that

consistent regulation of a legalized marijuana market would optimize price of the good,

essentially abolish the black market and allow for safer goods by regulating production

measures. The lofty question then becomes; what market structure would persist if the legal

retail market opened its doors? (Clark, May 2003) Critique this potential policy change by

addressing both a perfect competition market, as well as a monopolistic market. Their study fails

to suggest the most effective type of market, rather focusing on the price determination within a

legal market. (Clark, May 2003) Do however introduce some worthwhile questions regarding

the labor market as a result of their study. For instance, the labor wages would perceivably be

much lower within a competitive market, as opposed to the ability for a monopolistic firm to

control price determination, and in turn revenues – allowing for higher wages to be delivered to

their work force.

Consequently, (Barry, Hiilamo, & Glantz, 2014) warn us to be weary of the large scale

tobacco companies monopolizing this prospective retail marijuana market. According to (Barry,

Hiilamo, & Glantz, 2014), tobacco companies such as Philip Morris, British American Tobacco,

Brown & Williamson and RJ Reynolds have all been heavily involved in marijuana market

research since the 1970’s; suggesting a fervent need to structure a legal marijuana policy that

would exclude these (and other’s alike) large corporations from taking a stranglehold of the

market. They cite that in 1970, the U.S. Department of Justice actually funded a research

alliance with Philip Morris to conduct marijuana explorations of the unknown good. The then

5


president of Philip Morris, Ross Millhiser highlighted that this proposal “would allow PM to

learn about this potentially competitive product- and under impeccable sponsorship” (Barry,

Hiilamo & Glantz 2014, 213). Research confirmed the complimentary nature of the tobacco

(which these firms were obviously concerned about) and marijuana. Their findings began to

spurn profit maximizing ideas as exemplified by British American Tobacco internal documents

from 1976: “if the use of such drugs was legalized, one avenue for exploitation would be the

augmentation of cigarettes with near sub-liminal levels of (marijuana)” (Barry, Hiilamo &

Glantz 2014, 216-217). Furthermore, this exert exemplifies the extensive knowledge these

companies were privileged to in the late 70’s (especially for marketing purposes), emphasizing

the threat their competitive advantage poses to them controlling a retail pot market:

“Among youths ages 12-17 years, 11.5% smoke marijuana and 12.4% smoke cigarettes. Cigarettes are a “gateway” drug to marijuana use. Cigarettes are addictive because of nicotine; marijuana can cause dependency because of psychoactive cannabinoids. Teenagers who smoke cigarettes are 11 times more likely to become marijuana smokers.

There are an estimated 20 million current marijuana smokers in the U.S. of whom nearly 3-million are adolescents. More than one third of high school students have used marijuana in the eighth grade or earlier.” (Barry, Hiilamo & Glantz 2014, 225)

The most relevant issue regarding retail marijuana use that hasn’t been discussed is the

cash business aspect. In 2012, recreational marijuana use was in fact legalized in a few distinct

American states. Among those states, Colorado seems to draw the most attention for the policy

implementation. In the article (The New York Times, 2015), author Matt Richtel acknowledges

the gargantuan dilemma of the cash only business that is retail marijuana. The simple truth that

exists with legalized recreational use at the state level, is that federally, any sales, revenues and

profits are still seen as illicit cash activity (Pyke, 2015). This last point becomes crucial, as

existing and prospective retail marijuana dispensaries don’t have the ability to establish a

business bank account with most, if any banks; as banks won’t put themselves in such a risky

position to be complicit with illegal drug activity if the federal government were to conduct

investigations (The New York Times, 2015). But beyond this, (Pyke, 2015) indicates that the

cash only business puts everyone involved at risk. For one, the dispensaries are forced to hold

all cash flows in actual cash; making them high target assets to theft and robbery because of their

constant cash holdings. In an exert from an interview with a Denver marijuana dispensary

6


owner, (Pyke, 2015) explains that “the threat of robbery (factors) into almost every business

decision. (The owner Jaime Lewis) rotate(s) pay schedules for employees, and rotates pickups

for customers”. (Pyke, 2015) goes on to explain that although Colorado’s black market is

withering, “many of the people who have replaced it still find themselves riding around with

personal bodyguards and suitcases full of cash”. And these bodyguards are not the typical

pepper-spray carrying individuals. In most cases, they are highly trained, converted ex-military

individuals who now provide privatized security protection for obscure prices. Another

Colorado dispensary owner acknowledges that he dishes out at least $100,000 USD (The New

York Times, 2015) a year in security expenses for his business (keep in mind that’s also cash).

The article continues to highlight further individual security threats the cash business presents.

This side of the business is clearly closely related to the social welfare of the citizens which was

discussed earlier.

In fact, the few banks willing and legally able to associate with marijuana operations are

small, state-specific banks that don’t operate outside of their given pot-approved state. (Business

Insider, 2015) Identified a Bloomberg report announcing just 220 of America’s 7600-plus banks

and credits unions are accepting deposits from cannabis businesses. What becomes the issue is

these small banks charge colossal fees for the owners who bank with them; since the

investigative work on the banks end to ensure they won’t be complicit with illegal activity is

much larger than non-marijuana accounts. The same article suggests that recreational sales in

Colorado generated at least $700 million USD in 2014. With that much accessible cash, it’s

understandable why dispensary owners are aggravated with the unwillingness of banks to

associate with them. From the consumer side, all transactions must be made in cash as well.

Which means no credit card and no debit card transactions; a dilemma which irritates the

clientele no doubt. All of this frustration over the inability to bank the pot industry led to one

father and son duo filing through the process to create their own marijuana credit union; where

the purposes would predominantly be centered on banking with dispensary owners (The New

York Times, 2015) & (Barcott, 2015). Mark and Alex Mason, originally from North Carolina

traversed through a lengthy two year process of federal court denials to establish Fourth Corner

Credit Union, with one judge ruling saying “I would be forcing the reserve bank to give a master

license to a credit union that serves illegal businesses” (Barcott, 2015). It appears that there are

still problems that persist within the credit union’s approval as a quick glance at The Fourth

7


Corner Credit Union’s website clearly states the credit union is “Not Currently Open for

Business” (TFCCU - Denver Colorado, 2015).

REGRESSION ANALYIS: RESEARCH METHODS

The following analysis will be conducted by using OLS Regression Technique. In the

beginning, the question was posed; can we successfully identify predicting variables of Retail

Marijuana sales that may allow us to gage the health of the legal marijuana market? As

creational marijuana has been legalized in Colorado since late 2012, the data we will be

considering mainly deals with the state of Colorado and the Denver county area. This is simply

due to the readiness and availability of marijuana sales levels, as opposed to trying to determine

sales levels in states where the use is still illegal. Throughout the process, the objective will be

to obtain the regression model which seems to explain the variation in Marijuana sales the best

by critiquing the Adjusted-R2 values, as well as the overall significance (F-tests) and the

individual significances of each independent variable (t-tests). By the end, we hope to obtain a

model where all independent variables are statistically significant, and the overall fit has strong

explanatory power.

DATA DESCRIPTION

Retail Marijuana Sales

These sales levels depict the overall gross sales in USD (not inflation adjusted) for legal

recreational marijuana in 2014 and 2015. The data was presented in monthly fashion, where we

summed the quarterly amounts for our dependent variable. The sales levels were obtained from

opencolorado.org and are specifically reported from the Denver country area; as recreational

marijuana use and sales were legalized prior to 2014. It should be noted that gross sales for the

final three months (i.e. the last quarter) 2015 had not been reported yet; as a result, we used a 3-

month Moving Average (MA3) forecasting method to approximate the dollar value for gross

sales in this period.

8


Philip Morris Closing Stock Quote

Philip Morris International is the leading tobacco producer in the United States. Their

corporate website reports that they own a 51.3% market share of all tobacco production and sales

in the US. The original attempt was to include general tobacco sales levels (similar to the

dependent variable marijuana sales) because the good’s constant inter-connectedness as a

substitute or compliment with pot most literature. However, locating such data, specific to

Colorado or Denver, proved to be very difficult. As a result, we turned to the closing stock

quotes for this majority market owner company as a proxy that represents the overall

performance of tobacco sales in general. Since stock prices tend to represent the past, current

and expected future performance of the company they represent, the theory here is the higher the

closing stock price, the better the company is performing; hence, the overall tobacco market must

be performing well. The opposite would be assumed with relatively lower stock prices. The

quotes are reported in USD as traded on the NYSE:PM. The quotes were retrieved electronically

from CNBC’s financial reports on the New York Stock Exchange history. The data was

collected between 2014 and 2015 quarterly. From recent literature, if the relationship is

statistically significant between cannabis and PM stock quotes, I would expect them to share a

positively correlation; signifying a complimentary good.

Anheuser-Busch Closing Stock Quote

With similar reasoning as the Philip Morris stock proxy variable, the Anheuser-Busch

closing stock prices were included to serve as a proxy for the over alcohol market performance.

In the US, Anheuser-Busch self-reports a staggering 46.4% market share of all alcohol related

production and sales. The stock itself trades under NYSE:BUD and the data was collected

between 2014 and 2015 quarterly from CNN’s online financial database. In contrast to tobacco

goods, I would expect a statistically significant alcohol proxy variable to have an inverse

relationship with retail marijuana sales; signifying a substitute good.

Consumer Price Index

CPI offers economic evaluators the opportunity to critique what consumers are paying for

certain bundles of goods within a market. As a result, the index that is measured also allows us

to evaluate the value of the dollar within the market; hence the amount of goods that can be

9


consumed with relatively similar consumption ability. In theory, if the CPI were to increase, we

would expect a negative reaction in total gross marijuana sales, as an increase CPI signifies

higher costs for the bundle of goods available. This collection of CPI’s represents the values

from the Denver-county area in 2014 and 2015 and were reported monthly, but were collected at

each quarters end.

Medical Premium Expenses

Our fourth independent variable is the total expenditures on medical premiums by

individuals for the whole state of Colorado between 2014 & 2015 in real USD. The data was

reported monthly, but was summed to create quarterly totals for this time period. It should be

noted, that the final four months of data in 2015 were absent, as a result, we used a MA(3) to

compute the expected monthly values and consequently the final quarterly values. In respect to

performance, this category was included because plenty of literature highlights the potential

long-term health threat of smoking cannabis (as well as tobacco). Therefore, we would assume

that an increase in medical premium expenditures is positively correlated with marijuana gross

sales because we believe people are increasing their health coverage as a result of increased risky

behaviors.

State GDP

We obtained Colorado’s Gross Domestic Product from the Bureau of Economic Analysis

as a measure of the state’s overall economic health. Because retail marijuana has been legalized,

it should be recognized, legally, under the state’s GDP. Thus, we should expect a direct, positive

correlation between an increase in Colorado’s overall GDP represented in Millions of USD) and

retail marijuana gross sales levels. This data was reported quarterly for 2014 & 2015, and we

used a MA(3) forecasting method to predict the final two quarters of absent data. Also worth

noting, is the retrieved data had already been seasonally adjusted by their respective annual rates.

Income per Capita

Lastly, per capita income was included as an original independent variable to try and

explain the buying power of consumers within the market. We would assume to see a positive

correlation between an increase in per capita income and total marijuana sales as it is expected

10


that more disposable income results in a consumer purchasing more of the good. This piece of

data is representative of all of Colorado, between 2014 and 2015. The collected data was

reported at the end of each quarter in current USD from the Bureau of Economic Analysis and is

not adjusted for inflation.

NOTE – for all descriptive statistics see Appendix

FINDINGS

Initially, our first model (Model 1) included all of our independent variables described

above. Below are the regression outputs:

Model 1: β0+β1 PM 1+ β2 AB2+β3 CPI3+β4 M 4+β5GDP5+β6 I 6

Immediately in our analysis, we notice none of our independent variables, via a simple t-

test prove to be significant. This is very strange that none of them are significant, with such high

expectations from literature that at least one or two variables would show a significant

relationship with gross marijuana sales. What is more perplexing is our F-stat proves to be

significant and our Adjusted-R2 has some very strong explanatory power. This issue will be

11


discussed in more detail shortly. For now, the logical process we followed was to individually

regress each independent variable to see if any of them are truly statistically significant to gross

marijuana sales. Here are the output tables for each individual variable with the important values

highlighted:

12


13


By evaluating each independent variable individually, we can clearly determine which

variables have statistical significance to our dependent variable. As we can see, our variables for

Philip Morris and Anheuser-Busch fail to have any statistical significance with gross marijuana

sales. Each remaining variable does possess some level of statistical significance with our

dependent variable. Thus, our next step is to combine all individually significant independent

variables (omitting Philip Morris & Anheuser-Busch variables) into our second model in efforts

to predict gross retail marijuana sales:

Model 2: β0+β3 CPI3+ β4 M 4+ β5 GDP5+β6 I 6

14


Initially, we see very similar results in model 2 as we came across in model 1; that is to

say, not one significant independent variable, coupled with a significant F-stat and a very strong

goodness of fit according to our Adjusted-R2. In addition, we know that each independent

variable on their own are significant with our dependent variable. This leads me to believe that

there must be some problem with multicollinearity within our independent variables. Or more

simply put, some, or all of our independent variables are too highly correlated with one another.

Because of their correlation, our overall regression is failing to produce any significant results.

A correlation table (below) allows us to see that this in fact the problem we are dealing with.

At this point in time, we could revisit our original data and perhaps take a slightly

different approach with what other relevant data we could pull. Fortunately, with

15


multicollinearity, usually omitting one of the correlated independent variables from the

regression can fix this issue.

After a trial and error process, evaluating every other possible combination of our four

remaining independent variables (CPI, Medical Expenditures, GDP & Income) regression output

tables show no model with multiple independent variables that are all statistically significant.

This unfortunately means, for the sake of our analysis, that evaluating the health of the retail

marijuana market will rely solely on one independent variable (from the multiple we began

with). Based on the Adjusted-R2 values and the F-stats for each individual regression conducted

previously, the model which proves to show the best fit is that of Medical Premium

Expenditures:

Model 3 : β0+ β4 M 4

Where : M̂odel 3 : β̂0+ β̂4 M 4

M̂odel 3 :-535553650.80 + 11729.51527(M)

16


CONCLUSION

In summary, we visited many hot topics within the debate of legalized recreational

marijuana. Among the most intriguing arguments in support of the legalized use of retail pot, is

the economic benefit it provides for the overall economy; in the form of new jobs, additional

spending and the ability for a tax revenue from the legal sales of the good. It truly is an untapped

market with infinite profitability. And therein lies the issue, it must be a market which is

regulated properly, through proper taxation and avoidance of oligopolistic/monopolistic market

structures.

In regards to our regression analysis, following many computations, it appears that our

model which presents the best fit for our gross marijuana sales data is a very simple model; that

is to say a model that best explains the variations in marijuana sales dollars is the subsequent

individual expenditures on medical premiums (as previously presented). We should note, that

the independent variable of per capita income also tested highly significant with serious

explanatory power (when it was the sole independent variable). It’s Adjusted-R2 value suggests

it would do an adequate job of predicting variations in gross retail pot sales, although not as

strong a job as medical expenditures. As a result, this model, at this point in time, serves us as

the best opportunity we have to measure the health of the retail marijuana market by being able

to account for 91.1422 % of the variations in gross cannabis sales.

FURTHER INVESTIGATION

There may have been a few downfalls in our procedure which resulted in our final model.

Notably, the first is the selection of correlated independent variables which made the analysis

slightly difficult to manipulate. Second, with the relatively short amount of time that retail

marijuana sales have been legalized, our pool of data is fairly shallow. Therefore, revisiting

these data points in three to five years may prove much more significant. Third, because of the

availability (or lack thereof) of data, our moving average forecasts may have skewed certain data

points just enough to point them towards insignificant and unreliable results.

17


I would also like to draw some further attention to a model involving the independent

variables of medical expenditures and GDP. Although this model proved to only show one

statistically significant variable (Medical expenses), it was disregarded for it explanatory power.

However, a closer look may lead us to believe (especially with more extensive data in a few

years) that this could be the best fit model for in this given instance. The reasoning behind this

statement lies within the regression output below. As one can clearly see, the F-stat proves an

overall significance and the Adjusted-R2 show serious explanatory power. As mentioned,

medical expenses are significant, and GDP is not. However, because of potential data flaws (see

last paragraph) if we tested this regression at a different alpha level with new data points we

could conclude a different significant model than what we have. In any event, this entire

analysis would be more than worth revisiting in five years when retail marijuana sales have been

legal for an extensive period of time.

SUMMARY OUTPUT

Regression StatisticsMultiple R 0.968982R Square 0.938927Adjusted R Square 0.914497Standard Error 3531003Observations 8

ANOVAdf SS MS F Significance F

Regression 2 9.584E+14 4.79E+14 38.43436 0.000922Residual 5 6.234E+13 1.25E+13Total 7 1.0207E+15

CoefficientsStandard Error t Stat P-value Lower 95%Upper 95%Intercept 99942895 150850772 0.662528 0.536947 -2.9E+08 4.88E+08Total medical premium expenditures 44.63318 11.2545974 3.965773 0.010681 15.70231 73.56404All industry total COL GDP(millions USD) -663.23 601.512088 -1.1026 0.32042 -2209.47 883.0064

18


APPENDIX

Actual Data Sets for Variables:

Month/Year Retail M Sales Philip Morris stock priceBusch stock price CPI2014 q1 27,975,800.99$ 81.87$ 106.63$ 72.60q2 35,177,612.77$ 84.31$ 115.65$ 92.70q3 43,908,047.75$ 83.40$ 107.45$ 86.10q4 42,280,351.22$ 81.45$ 111.74$ 102.802015 q1 46,476,251.74$ 75.33$ 125.71$ 104.40q2 55,381,650.35$ 80.12$ 121.96$ 111.50q3 61,227,020.98$ 79.33$ 110.04$ 125.20q4 61,653,980.84$ 87.91$ 125.00$ 97.40

Month/Year Total medical premium expenditures All industry total COL GDP(millions USD) COL per capita Income Total USD2014 q1 2,790,163.00$ 297,034.00$ 48,075.00$ q2 3,078,694.00$ 303,425.00$ 48,649.00$ q3 3,264,007.00$ 309,520.00$ 49,009.00$ q4 3,398,396.00$ 313,504.00$ 49,707.00$ 2015 q1 3,576,573.00$ 312,003.00$ 49,994.00$ q2 3,695,492.00$ 316,535.00$ 50,469.00$ q3 3,758,890.00$ 314,014.00$ 50,828.00$ q4 3,760,339.15$ 314,184.00$ 50,430.33$

19


20


Works CitedBarcott, B. (2015, December 30). Shh! Here's How Cannabis Campnaies are Banking Legally on the Down Low.

Retrieved February 15, 2016, from www.Leafly.com.

Barry, R. A., Hiilamo, H., & Glantz, S. (2014). Waiting fo rthe Opportune Moment: The Tobacco Industry and

Mrijuana Legalization. The Milbank Quarterly, 207-242.

Bates, S. W. (2004). The Ecnomic Implications of Marijuana Legalization in Alaska. Fairbanks, AK: Boreal Economic

Analysis & Research.

Business Insider. (2015, November 12). This could be the No.1 problem faving legal weed businesses in America. p.

2.

Clark, A. E. (May 2003). The Economics of Drug Legalization. Paris, France: CNRS & DELTA.

Clements, K. W., Lan, Y., & Zhoa, X. (2010). The deman for marijuan, tobacco and alcohol: inter-commodity

interactions with uncertainty. Empirical Economics, 203-239.

Geller, A., & Fagan, J. (2010). Pot as Pretext: Marijuana, Race and the New Disorder in New York City Street

Policing. Journal of Empirical Legal Studies, 591-633.

Pyke, A. (2015, August 11). Colorado's Pot Industry Shut Out of Banks, Forced to Operate Entirely with Cash.

Retrieved February 15, 2016, from http;//thinkprogress.org/economy.

Shanahan, M., & Ritter, A. (2014). Cost Benefit Analysis of Two Policy Options for Cannabis: Status Quo and

Legalisation. PLoS ONE, 1-12.

TFCCU - Denver Colorado. (2015). The Fourth Corner Credit Union. Retrieved 02 16, 2016, from

http://www.thefourthcornercreditunion.com/.

The New York Times. (2015, February 5). The First bank of Bud. Marijuana Industry in Colorado, Eager for Its Own

Bank, Waits on the Fed.

21

pot project - final

Documents