1. Albany International Airport Foot Traffic
by
Brian Pfaff
University of Oregon
Pfaff@uoregon.edu
10/7/2014
Abstract
This paper will be examining the foot traffic going on at the Albany
airport in New York from 1993-2010. This paper will examine as to what
causes an airport to have a high or low population during different times of
the years. The point of this project is to understand how to fully understand
stata and how to interrupt our results that have been acquired by stata.
Paper prepared
In
Partial Fulfillment of the Requirements of Economics 421
Keywords: ALB, Airport size, growth, and patterns.
JEL Code: R41

2. Introduction
The purpose of this project is to figure out as to why airports have increased
in size as in foot traffic over the past few decades. The airport that will be discussed
in this paper is the Albany International Airport in Albany, New York. U.S. nationally
along with the state of New York and the city of Albany cares about this issue, so
that they can know as to why the airport is increasing or decreasing in foot traffic
over the last few decades. They will also be able to know as to how they will be able
to make the Albany airport more successful. This is also a concern as to the airlines
that are currently flying in and out of Albany, and as to how they can better work
with the Albany airport. The contribution that will be given in this paper is the fact
that it will hopefully solve the reasoning as to why the airport has been successful or
not. What I hope to find by doing this project is to find the contributing factor as to
what makes an airport successful or not. I hope to conclude that there are a few
contributing factors that truly make an airport successful, and to the reasons as why
Albany foot traffic has been declining over the past few years.
Outline
Background
History of Albany International Airport. Major events that happened at the
airport.
Theoretical Model
Explaining what type of model is used in this paper, and why it is important
that the model used is the correct model.

3. Empirical Model
The actual model used and explained in math term what the model is doing.
Data
The actual data that is resulted from the empirical model
Results
Explanation of the data and what it means in terms of my model, and what
the paper is trying to answer
Conclusion
Summary of what the paper is about, and overall conclude the paper and
what could happen in the future for Albany International airport.
Background
Albany International Airport was the first municipal airport in the United
States. It was founded on May 29, 1910, and was the first takeoff location of the first
sustained flight from Albany to the city of New York1. The takeoff location of the
airport was on a farmland around Albany, New York. In 1928 the construction of
the airport in Albany, which was on a Shakers farmland, began1. In 1939 the airport
was closed for being “unsuitable for use.” The city made improvements and in 1942
was reopened, and has stayed open ever since1. Over the existence of the airport, it
has been threatened multiple times that it was going to be shut down, but it has
remained open since 19421. As of now, the airport is 1,200 acres, and is open 24
hours a day. The airport recently finished and multi-million dollar renovations and
updates to facilities such as 230,000 square foot terminal, parking garage, air traffic
1 http://flyalbany.com/about-alb/welcome

4. control tower, and a cargo facility1. There are 10 different airlines that go in and out
of Albany International Airport1. The daily commercial arrivals and departures are
about 90 each or 180 arrivals and departures. There are 20 different operating
gates at Albany International Airport1.
Theoretical Model
Albany International Airport over time has increased a solid amount, but as
of the last 10 years has steadily began to decline. The major reasoning for the
decrease in foot traffic over the past decade is due to the number of hubs decreasing
over time. From 1993 till 2005 there were 5 hubs that were using Albany
International Airport as a transfer stop1. Then from 2005 to 2008 the number of
hubs was 4 and then in 2009 the number decreased to 31.
The airlines that go in and out of the airport are Cape Air, Delta Air Lines,
Southwest Airlines, United Airlines and US Airways. The nonstop flights that fly out
of Albany go to 16 different major locations1. Relatively speaking Albany
International Airport is small airport that flies to a few bigger airports. Since the
airport is small the planes flying in and out of the airport tend to be smaller which
means that flights tend to be more expensive. Flying is a luxury good, mix that in
with even more expensive flights, and the number of hubs decreasing over the past
few years is a good indicator for why the foot traffic has decreased over time. The
city of Albany and the cities around it are all relatively small with Albany has a
population of just under 100,000 as of 2014 with an average income of just under

5. $40,0002. Since this airport is small and around a smaller city people are not flying
in and out of it as frequently as they would be if it was located near a huge city for
business.
Empirical Model
Passengers= β1 + β2income_20 + β3hubs + μi. This is the model that I have
come up with to help explain the foot traffic going on in the Albany International
Airport. This model takes into account income within 20 miles of the airport along
with the number of hubs using Albany International Airport as a major stopping
point. The Albany Airport is not as big as an airport for the business people as is
other airports in the New York area. There is a good amount of measurement error
in the equation. Such variables cannot be accounted for such as jobs around the
area. I believe there will be measurement error because the values will not conform
to an exact relationship, therefore there will be discrepancy to the disturbance term.
Not knowing the jobs of people, which could explain reasons as to why the airport
has been declining recently. There is heteroskedasticity and the mean disturbance
term will be zero and will have constant variance.
Data
The primary source of data used for this analysis is from the Bureau of
Transport statistics 10 percent origin-destination survey.3 From this data,
passenger origins are developed for ALB airport by aggregating all passengers that
originate from this airport. These data were supplemented by income and
2 https://suburbanstats.org/population/new-york/how-many-people-live-in-
albany
3http://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/subject_areas/airline_info
rmation/accounting_and_reporting_directives/number_143.html

6. population statistics obtained from the Census Bureau’s “Small Area Income and
Poverty Estimates” which provides data for population and income at the country
level for 1993, 1995, and 1997-2009.4 The missing years were interpolated from the
neighboring years. From the St. Louis Fed, a consumer price index was obtained to
deflate the monetary variables. The data about the number of hubs present during
certain years was obtained from Albany International Airport’s history page1.
The dependent variable is defined as passengers, which is the amount of
people coming in and out of the airport. Following the empirical representation of
the theory and empirical model, origins are explained by the average income of the
population within 20 miles from Albany International Airport, and the amount of
hubs that uses Albany International Airport as a stop over place. The amount of
hubs is a numerical number between 5-3, and it is expected that as the number of
hubs goes down that the number of passengers go down too.
4 http://www.census.gov/did/www/saipe/
1 http://flyalbany.com/about-alb/welcome

7. This graph represents the trend of the amount of passengers given during a certain
quarter starting since 1993. All the way up until 2005, there was a steady increase
in passengers as the years went on.
This is a scatter plot of the average income within 20 miles from the Albany
International Airport. For my regression I regressed passengers on income within
20 miles and the number of hubs located at Albany International Airport.
Results

8. The results that I have gathered from my data is that equation 3 is the
equation is the most fitting, which just takes into account income within 20 miles of
the airport and the amount of hubs that are present there. Every variable in this
equation is statistically significant at the 99%. Even though quarter increases the R-
squared it shows no significance in my equation. This result matches my data
because as hubs go up passengers’ foot traffic goes up. Over the past few years the
hubs have decreased from 5 to 3 so like wise passenger foot traffic has gone down.
Equation 3 best fits my model as to why for many decades foot traffic was increasing
in Albany Airport because of income, but as the hubs went down the foot traffic did
too.
Conclusion
Overall, if Albany International Airport does not increase its hub numbers
then the foot traffic will remain minimal. There are very few flights that fly into and
out of Albany International Airport and that can be contributed to the amount of
hubs located at the airport. Albany International Airport is not a convenient airport
to fly into and out of and because of its low number of hubs flights are increasingly
more expensive. The reason why Albany International Airport has been decreasing
has been due to hubs and relatively the same income level.