1. Gun Storage Policy and the Evaluation of Student Willingness to Pay
Wesley Turner
2. Introduction:
“Rifles, shotguns, crossbows, compound bows and longbows with field or broad head
points are permitted in residence halls; however, they must be stored in the hall firearms storage
facilities.” (Brown and Bondy pg. 38) The policy previously provided is currently in effect at
Montana State University. It is rare for public universities to offer a service such as gun storage
within campus residence halls. Currently this service is treated as a service good that is suffering
from surplus of demand by the students that live on campus. This service can be determined as
over used because of the limited storage area available for use and students are required to use
the storage if they have a firearm with them during the school year. It is the goal of this paper to
determine if Montana State students have high enough willingness to pay for gun storage use and
creation of an aggregate demand curve. This will be accomplished using the demand created
from the willingness to pay, the existing supply, an ordinarily square (OLS) model to evaluate
the market, and benefits the introduction of fee along with this policy may produce.
Background:
The gun storage policy has been in effect at Montana State University since prior to 1995
(Bondy 2015). Montana State University resident hall students have access to five gun storage
facilities across campus. It is the assumption of this paper that this policy was put into place to
accommodate the gun owners who wanted to keep their guns with them for hunting and
recreational use. Cook et al. report in their 1995 paper that 59% of households nationally have a
firearm present. Storage is a required service for the students that do bring guns to Montana State
because it allows for a safe secure location, prevents misuse, and alleviates some of the dangers
present with gun ownership. Such dangers that come with guns being present in residence halls
include criminal activity, suicides, and accidental misfires that could lead to injuries or
3. damages. Many researchers have looked into the effect guns have on violent crimes and suicides
(Ayres and Donohue 2009, Cook 1981, Cook et al. 2001, Moody and Marvell 2005, Southwick
1997) and findings differ between researches if guns have a strong effect on crime. In their 2005
paper Moody and Marvell report that if handgun ownership was reported in 26% to 52% of
households, it would lead to an increase in crime by 1%. In Southwick’s 1997 paper, he finds
similar results that guns have no significant effect on aggravated assault or robbery in the
regression used in his research. Regulation of the gun market is often times the action taken by
local and federal government leading to researchers conducting studies into discovering if these
regulations have a significant effect in reducing crime and misuse (Cook, et al. 1995). As
suicide is the third leading cause of deaths in ages ten to twenty four (College Health and Safety
2014), Residence Life could be concerned that firearms not stored in a safe location could cause
mentally unstable students use a firearm as a tool for suicide. In their 2001 paper, Lott and
Whitley report that there is no significant evidence that access to guns increased the likelihood a
person fifteen to nineteen years old would attempt suicide.
Data:
Due to location specific variables and the unique policy that is enforced in the Montana
State University’ residence halls, there is no prior data that exists pertaining to this researcher’s
question. In an ideal world the creation of a panel dataset of students living in the residence halls
would occur. This dataset is ideal because it focuses on students that are currently affected by the
policy for multiple periods of times. Over time, students’ thoughts on this policy change could
become different as their taste and preferences evolved. Due to limited time and resources the
creation of this dataset was impossible. Instead this research uses a cross-sectional dataset that
takes a portion of the Montana State student population. All students that attend the institution
4. were included in the population of focus because a large portion of students have lived in the
residence halls for at least one semester. This also allows for changes in students’ taste and
preferences to be accounted for because a majority of individuals who live in the residence halls
are freshmen or sophomores. Including the full population of the institution allows a larger
partition of upper-classmen to be included in the sample.
To create a cross-sectional data set a survey was handed out and collected at major traffic
point on campus to passing students. On this survey two ways to determine willingness to pay
for gun storage was used; an example of this survey is given as a part of Appendix 1. The first
method used was a dichotomous choice where the individual was asked if they were willing to
pay a randomly assigned number between five dollars to forty dollars. This type of question
produced a bimodal distribution of the respondents and the percentage of compliance for each
bid offered is broken down in Table 1. The second method used to determine willingness to pay
was an open ended question where the student was asked what their maximum willingness to pay
for gun storage was. After the survey collection was complete the sample consisted of 206
observations with an average max willingness to pay of $26.23. Of this data set 56.31% owned a
firearm. This distribution allows for non-firearm owners’ preferences to be accounted for as the
storage may create a negative externality of fear. A more detailed breakdown of this dataset’s
summary statistics and variable names is given in Table 2. This data set included thirty nine
observations that had not lived in the residence halls and because of this a second dataset was
created that only included students that currently live or have lived in the residence halls at
Montana State University. This second dataset was made up of 167 observations that had the
mean max willingness to pay of $26.36. Table 3 provides summary statistics of the second
dataset. Currently there is only a small change in the willingness to pay with the non-campus
5. housing students. In both datasets the maximum willingness to pay had a max of two hundred
dollars. It was unexpected to see a large response such as this with students who have limited
incomes and other goods and services that could take large portions of that income.
Empirical Framework:
This research uses two different methods to evaluate the willingness to pay for gun
storage in the residence halls. The first method used to evaluate the samples willingness to pay
was by calculating the mean willingness to pay using the data collected with the dichotomous
question. Along with this method an evaluation of the existing systems supply and demand was
done. This evaluation allowed for building and understanding what the current market
equilibrium is as well as it enabled the confirmation that the good is overused by participants.
Using the data from the dichotomous variables to derive the samples demand curve, it was
compared to the existing quantity demanded by students living in the residence halls. As a part of
this evaluating process a logistic regression was performed using the dichotomous choice data.
Model 1 depicts the equation used in the logistic regression.
Model 1: Prob(C=1) = [exp(βBidi)]/[1-exp(βBidi)]
In this logistic regression the binary dependent variable used was compliance where C=1 if the
response was “Yes” and C=0 if response was “No”. The logistic regression was performed
because the independent variable Bid has a non-linear relationship with compliance in Model 1.
Using this type of regression allowed an odds ratio of paying for gun storage to be derived.
The second method to evaluate the willingness to pay for gun storage was performing an
ordinary least square regression. The OLS regression was performed using the max willingness
to pay data from both data sets because this variable was more fluid as it is a continuous variable
that ranges from zero to two hundred dollars. This paper hypothesis that if the student graduated
6. high school from a secondary institution in Montana, the student’s max willingness to pay will
be less than a student that graduated in another state. This research believes this occurs because
individuals that have lived in Montana are more likely to own firearms. The first OLS regression
performed on the two datasets is a simplified model that only included the two variables of
concern. This approach is represented by Model 2.
Model 2: MaxWTPi =β0+β1Montanai+εi
The max willingness to pay variable is untransformed to keep the model simple. Montana is a
binary variable, that is broken into a 1 or a 0 dependent on if the student graduated from a
secondary institution in Montana (1 for a Montana graduate, 0 otherwise). Due to sever missing
variable bias several variables were introduced into a more complex model, represented by
Model 3.
Model 3: MaxWTPi =β0+β1Montanai + β2Agei+ β3Ownershipi+ β4PaymentKnowni+ β5Westsidei+
β6Upperclassmeni+ εi
The variable of age was included in the model because students gain access to larger range of
firearms as they increase in years. An example of this is occurring is when the individual turns
twenty one they are able to purchase pistols. Ownership is a dummy variable that represents if
the individual currently holds any firearms. The correlation between firearm ownership and the
students graduating from a secondary education provider in Montana is relatively strong, if
ownership was excluded this could cause the estimation to underestimate the true effect. On the
survey within the max willingness to pay question a change in wording is present. Each student
who was surveyed was randomly given knowledge of how the fee would be paid; this is
represented by the variable PaymentKnown. PaymentKnown is a binary variable where 1
represented a student who knew that the payment would be made through the students’ accounts
7. office, similar to tuition and other institution fees from Montana State. If this information was
not provided to the individual, it was represented by a 0 value. Including the PaymentKnown
variable was important to the model because students who think this fee is included along with
tuition and other fees may have a greater willingness to pay then students who think otherwise.
The rationale behind this is that students who know the payment knowledge may not currently
put the cost to themselves.
On campus there are seven residence halls but only five of these halls have the ability to
house firearms, a majority of which are located on the Westside of campus. The Westside of
campus also houses the majority of students that live within the halls. Due to these issues the
dummy variable Westside was used because students with greater access to the storage areas
may have a lower willingness to pay for its use. Since over time taste and preferences change
with the growth in an individual’s education this effect was captured using a dummy variable
where a value of 1 represents students that have attend Montana State for three years or more and
a value of 0 indicates students that have attend for 2 or fewer years.
Results/ Discussion:
Using the information collected from the dichotomous question on the survey Figure 1
was constructed. From Figure 1 one can see that the data collected produced a bimodal
histogram, where the two peaks occur at five and twenty five dollar bids. As predicted the lowest
bid produced the highest percentage of compliance; while the second peak of the histogram was
unexpected the data did follow the negative relationship. After each peak the percentage of
compliance following bids decreases. Currently the resident hall storage facilities host five
hundred plus firearms. North Hedges has the largest facility with storage space for sixty guns or
bows to be stored properly and safely (Bondy 2015). During the spring semester North Hedges
8. housed 118 firearms in its storage area. Using this information to construct a supply curve
represented in Figure 2, it demonstrates an inelastic supply curve. Figure 2 represents the supply
of Firearm storage using the assumption that there is only a finite number of storage spaces
which will always offer that quantity no matter the price to use the storage. Using the
dichotomous data an approximate willingness to pay of $26.26 was calculated. Using this
willingness to pay as a benefit from North Hedges residence hall, the largest storage area with
largest demand of 118 firearms, the revenue will be $3098.68. Comparatively if the mean of max
willingness to pay was calculated it comes out at $26.23, which is very similar to the
approximate willingness to pay calculated earlier. In Figure 3 a distribution of student’s
willingness to pay is shown and both max and approximate willingness to pay calculations fall
within the third quartile of Figure 3. This indicates that the calculations are on the right path of
determining the true willingness to pay for students at Montana State University. Table 4 reports
the findings from the logistic regression. The coefficient reported indicates that an individual’s
log-odds in the dependent variable of compliance decrease by 0.02 as the bid variable increases
by one unit. This finding is statistically significant at an alpha level of 0.1. This falls within the
economic theory of law of demand which states as price increases the quantity demanded for the
product should decrease. Given this information this research is able to assume that the demand
for firearm storage has a negative slope curve and is not a giffen good. This falls in line with the
down ward sloping sections of Figure 1.
Table 5 reports the results of the OLS regression. In column 1 of Table 5 the sex of the
individual is not controlled for within the model. In column1, one is able to see that graduating
from a secondary school in the state of Montana decreases the max willingness to pay of the
individual by $6.59. In order to determine if being female affected the dependent variable a
9. second regression was performed controlling for the individual’s sex. These findings are reported
in column 2 of Table 5. In this second regression the individual’s max willingness to pay if
graduated from a secondary school in Montana decreases by 6.92, however the effect from the
individual being female was statistically insignificant. In both columns 1 and 2 age was the only
other statistically significant effect being negative in both as the individual increases in age by a
year. This research predicted that if the student knew how the fee was being paid it may increase
the individual’s willingness to pay, however if the student knew that this fee was being charged
to their student account it had a negative effect. This may because the student is aware this
means it is being applied to their individual debt or they are unaware what student account is.
As this policy only affects students that live within the residence halls of Montana State
the next step in the analysis of willingness to pay was to drop any observations that did not
confirm that they lived in the halls while attending post-secondary school. Following this, two
more regressions were performed. In column 1 of Table 6 there is no control for if the individual
was female or not. In this column one can see that a student’s willingness to pay decreases by
$9.22 if the resident graduated from a secondary institution in Montana. Similar to the findings
in Table 5 age has a negative effect on the individual’s willingness to pay for firearm storage but
the decrease for the one addition year is greater in Table 6. However when all observations that
did not live in the Montana State University residence halls were dropped another variable that
was controlled becomes significant. This variable was ownership. When there is no control for if
the individual was female, the individual’s willingness to pay increase by $7.83 if he/ she owned
a firearm. In column 2 of Table 6 the effect increases to $8.47 while still having a positive
relationship between gun ownership and max willingness to pay. This increase in the effect could
be contributed to the fact that students who have lived in the halls have a greater understanding
10. of the policy or are more affected by the fee. When the regression controlled for if the individual
was female the effect from if the student graduated from a Montana high school increased to
9.44, still a negative relationship. All other controlled variables besides age, and firearm
ownership were statistically insignificant. In all four regressions performed the main relationship
of interest in this paper is statistically significant at an alpha level of 0.1.
Conclusion:
Since firearm ownership and use is a significant subject in many parts of the world
because of the dangers it presents, storage is an important factor to determine if an individual is
capable to own one responsibly. Based off the findings in this paper one can concluded that there
is a willingness to pay for storage in the residence halls present. It can also be concluded that
graduating from a secondary education school in Montana decreases the willingness to pay for
storage use. The internal validity of this research is hurt slightly because during the time the
survey was being handed out the Montana State Legislature was voting on allowing open carry
on university campuses. As most students were aware of this potential policy change the effect it
had on the estimates found should be relatively small. Due to the specificity of the data and
model used in this research there is little to no external validity. While in other research external
validity is important, in this research it is not, because of the policy in place at Montana State
residence halls can be considered a unique occurrence (not commonly found at other schools).
Although the assumption of normal distribution is not met by this data, this is easily rectified by
the creation of a larger dataset.
The results found in this paper indicate there is strong evidence that some students would
be willing to pay for gun storage. Even with this evidence, the recommendation to the Residence
Life leadership is to take no action to begin charging for storage. This recommendation is
11. because if Residence Life did introduce this policy change students may become more tempted
to sneak firearms into their rooms to avoid paying the storage fee. Although this potential cost is
not calculated it is safe to assume that if this action were taken by students negative externalities
would be produced decreasing the net benefits that would occur by introducing the fee.
If this research was to continue, a panel data set could be created; focused within the
residence halls giving the sample a larger standing and increasing the internal validity of the
research. If the new data set was used similarly it allows the estimates calculated to become
closer to their true value. As many states do allow for open carry on university campuses it
would be interesting to see if this policy had an effect on the criminal activity that takes place on
these campuses.
12. Appendix 1:
Currently the Resident Life Office of Montana State offers free firearm storage at a
majority of resident halls. The goal of this survey is to discover if there is a willingness to
pay for the firearm storage amongst Montana State University students.
Disclaimer: This Survey is being done outside the scope of the Resident Life Office
(ResLife) any information gained from it will not be shared with ResLife Staff. All the
following questions and policy changes are hypothetical and are not being implemented or
considered by ResLife.
If you were asked to pay the following fee per semester would you be willing to pay it?
$5.00 $10.00 $15.00 $20.00 $25.00 $30.00 $35.00 $40.00
Yes No
Suppose the residence halls were to introduce a policy of charging students a fee for firearm
storage. This fee would be charged to your student account once a semester and would cover up
to five firearms. What is the maximum amount you would be willing to pay?
Sex: Male Female
Age:
What state did you graduate high school?
Current Year in School: Freshman Sophomore Junior Senior Graduate
Do you live in or have you lived in the residence halls at Montana State?
13. Yes No
If yes which hall?
North Hedges South Hedges Roskie Freshman Apt
Hapner Hannon/ Quads Langford Johnstone
Do you own any firearms?
Did you store your firearm with the residence halls’ front desks?
If yes how many firearms did you store?
16. Table 1:
Bid Compliance (Percentage)
5 92%
10 65.38%
15 53.85%
20 57.69%
25 73.08%
30 65.38%
35 64%
40 53.85%
# of Observations 206
Table 2:
Variable Description Mean (Std. Dev.) Min Max
MaxWTP Maximum willingness to pay for
storage
26.23 (29.69) 0 200
Age The age of individual 20.78 (2.7) 18 36
Ownership Binary variable 1 if firearms are
owned 0 if otherwise
Storageuse Binary variable 1if firearm storage
was used 0 if otherwise
Montana Binary variable 1 if graduated from a
high school in Montana 0 if otherwise
Westside Binary variable 1 if live or lived in a
residence hall on the Westside of
campus 0 if otherwise
SqrtWTP The square root of MaxWTP 4.23 (2.9) 0 14.14
Upperclassmen Binary variable 1 if student is senior
or junior 0 if otherwise
Paymentknown Binary variable 1 if knowledge of
how payment is made 0 if otherwise
Female Binary variable 1 if individual is
female 0 if individual is male
# of Observations 206
17. Table 3:
Variable Description Mean (Std. Dev.) Min Max
MaxWTP Maximum willingness to pay for
storage
26.35 (29.94) 0 200
Age The age of individual 20.28 (1.82) 18 31
Ownership Binary variable 1 if firearms are
owned 0 if otherwise
Storageuse Binary variable 1if firearm storage
was used 0 if otherwise
Montana Binary variable 1 if graduated from a
high school in Montana 0 if otherwise
Westside Binary variable 1 if live or lived in a
residence hall on the Westside of
campus 0 if otherwise
SqrtWTP The square root of MaxWTP 4.29 (2.82) 0 14.14
Upperclassmen Binary variable 1 if student is senior
or junior 0 if otherwise
Paymentknown Binary variable 1 if knowledge of
how payment is made 0 if otherwise
Female Binary variable 1 if individual is
female 0 if individual is male
# of Observations 167
Table 4:
Column 1
Bid -0.02 (0.01)*
Coefficient 1.18(0.33)
Pseudo R2 0.0124
# of Observation 206
Coefficient (Standard Error) Standard errors accounted for heteroskedasticity **:significant at .05
alpha *: significant at .10 alpha
18. Table 5:
Column 1 Column 2
Montana -6.59(4.03) * -6.92(4.03)*
Female No Yes
Age -1.40(0.58)** -1.24(0.56)**
Ownership 4.68(4.16) 6.02(4.27)
Payment Known -4.73(4.08) -4.59(4.07)
Westside of Campus -2.13(3.880 -1.42(4.16)
Upper Classman -4.51(4.03) -4.47(4.02)
β 0 62.40(13.00) 55.82(12.22)
R2 0.04 0.05
# of Observations 206 206
Coefficient (Standard Error) Standard errors accounted for heteroskedasticity ***: significant at .01
alpha **: significant at .05 alpha *: significant at .10 alpha
Table 6:
Column 1 Column 2
Montana -9.22(4.33)** -9.44(4.37)**
Female No Yes
Age -2.65(0.97)*** -2.42(0.86)***
Ownership 7.83(4.66)* 8.47(4.87)*
Payment Known -6.70(4.50) -6.63(4.48)
Westside of Campus -1.72(4.06) -1.22(4.53)
Upper Classman -3.36(4.05) -3.75(4.25)
β 0 87.44(21.34) 81.19(18.65)
R2 0.07 0.07
Coefficient (Standard Error) Standard errors accounted for heteroskedasticity ***: significant at .01
alpha **: significant at .05 alpha *: significant at .10 alpha
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