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TRANSCRIPT
E S C A M B I A C O U N T Y
F L O R I D A
P O P U L A T I O N
F O R E C A S T 2 0 4 0
BEARDS & ASSOCIATES
APRIL 2014
ADAMS
ALMARIO
BRICKSER
DROUIN
SHAFFER
TAPSOBA
TORRES
JOSH
RAFAEL
C RAIG
JACKI E
WES
NINA
ORLANDO
E X E C U T I V E S U M M A R Y
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A 2040 POPULATION FORECAST FOR ESCAMBIA COUNTY, FLORIDA
This report provides a population forecast of Escambia County, Florida for the year
2040. Using population data from 1960 to 2010, a range of plausible projections guide our
forecast. Additionally, we consider economic and social trends that help explain the forces
shaping Escambia County’s population growth.
KEY FINDINGS
POPULATION TRENDS
From 1960 to 2000 Escambia enjoyed a steady growth of roughly 30,000. However, from
2000 to 2010 its population barely grew by 3,000 people. While shocking, this halt is only
the tip of the iceberg of a greater trend: since 1970, Escambia’s share of the regional
growth has been steadily declining, yielding to its neighboring fast-growing counties of
Baldwin and Santa Rosa.
This phenomenon can be partly explained by a variety of factors:
o First, the region is seeing a trend of decentralization and growth in the suburban
areas in the outskirts of the city of Pensacola. However, given Escambia’s thin
shape, much of this growth has taken place outside its borders.
o Second, the county has significantly higher crime rates than its neighbors. Indeed,
it has the highest rate in the entire state of Florida.
o Third, Escambia’s school quality is one of the poorest in the region whereas
neighboring Santa Rosa is one of the strongest in the state.
Having a much higher school grade, significantly lower crime, and more development,
Santa Rosa has become the most rapidly growing county in the region. Despite this, over
a third of their population works in Escambia. In that sense, Santa Rosa has become an
appealing “dormitory” county that is driving the growth in the region.
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ECONOMIC TRENDS
Escambia’s core industries are (1) tourism, (2) the military, (3) healthcare, and (4)
education. In the past decade, the county has experienced significant challenges
healthcare and tourism, both of them losing jobs between 2006 and 2011. The military
has continued to contribute to the county’s growth in a slow and stable manner while
education has grown considerably and shows promising signs.
FORECASTING
After its lackluster growth in the past decade, where the county barely grew by 1%, we
expect Escambia to grow at a slightly faster rate starting on 2020. However, there are no
clear signs that the economic and demographic forces driving growth out of Escambia
into its suburban neighbors will stop and, therefore, we do not expect Escambia to
recover its high growth rates typical of its previous decades leading to the turn of the
century. Our forecast predicts that Escambia will move from 297,619 residents in 2010,
to 320,793 in the year of 2040, growing at a rough average of 2.5% every decade.
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Table Of Contents
A 2040 Population Forecast For Escambia County, Florida .......................................................................... 2
Key Findings ......................................................................................................................................................................... 2
Population Trends ......................................................................................................................................................... 2
Economic Trends ........................................................................................................................................................... 3
Forecasting ....................................................................................................................................................................... 3
1.0 Background & Context ................................................................................................................................................. 10
1.1. Geography ................................................................................................................................................................... 10
1.2 History ........................................................................................................................................................................... 12
1.3 Key Places ..................................................................................................................................................................... 13
1.3.1 Municipalities ..................................................................................................................................................... 13
1.3.2 Census Designated Places .............................................................................................................................. 13
1.3.3 Military Presence .............................................................................................................................................. 13
1.3.4. Manufacturing ................................................................................................................................................... 14
1.3.5 Healthcare ............................................................................................................................................................ 14
1.3.6 Prison ..................................................................................................................................................................... 14
1.3.7 Higher Education .............................................................................................................................................. 16
1.4 Natural Resources ..................................................................................................................................................... 16
1.4.1 Groundwater: ..................................................................................................................................................... 16
1.4.2 Surface Water ..................................................................................................................................................... 16
1.4.3 Conservation Lands ......................................................................................................................................... 17
Parks .................................................................................................................................................................................. 19
Agricultural Land ......................................................................................................................................................... 19
1.5 Infrastructure.............................................................................................................................................................. 19
1.5.1 Major Roads ........................................................................................................................................................ 19
1.5.2 Bridges .................................................................................................................................................................. 21
1.5.3 Rail Roads/Port Of Pensacola ...................................................................................................................... 21
1.5.4 Airport ................................................................................................................................................................... 22
1.5.5 Wastewater Treatment Facilities .............................................................................................................. 22
1.5.5 Potable Water ..................................................................................................................................................... 24
1.5.6 Parks (86 County Parks) ................................................................................................................................ 24
1.5.7 Public Transit ..................................................................................................................................................... 25
1.6 Economic Trends ....................................................................................................................................................... 27
1.7 Major Attributes......................................................................................................................................................... 28
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2.0 Analysis Of Current Population .......................................................................................................................... 30
2.1 Population .................................................................................................................................................................... 30
2.1.1 Population By Decade For Escambia, Region, And State .................................................................. 30
2.1.2 Growth Rate For Escambia, Region, And State ..................................................................................... 32
2.1.3 Growth Rates By Year For Escambia And Region, 2000-2010 ...................................................... 35
2.1.4 Population Growth Outliers In The Region ............................................................................................ 36
2.1.5 Escambia County Population By Census Tract ..................................................................................... 37
2.1.6 Urban Areas ......................................................................................................................................................... 39
2.2 Demographics ............................................................................................................................................................. 40
2.2.1 Age And Gender ................................................................................................................................................. 40
2.2.2 Race And Ethnicity ........................................................................................................................................... 40
2.3 Group Quarters Population ................................................................................................................................... 44
2.4 Socioeconomic Indicators ...................................................................................................................................... 46
2.4.1 Socioeconomic Indicators Introduction .................................................................................................. 46
2.4.2. Educational Attainment ................................................................................................................................ 46
2.4.3 Unemployment .................................................................................................................................................. 47
2.4.3 Poverty .................................................................................................................................................................. 48
2.4.4 Crime In Escambia And Region ................................................................................................................... 48
2.5 Housing: ........................................................................................................................................................................ 51
2.5.1 Introduction To Housing ................................................................................................................................ 51
2.5.2 Housing Units ..................................................................................................................................................... 51
2.5.3 Vacancy ................................................................................................................................................................. 53
2.5.4 Housing Values .................................................................................................................................................. 55
2.5.5 Households .......................................................................................................................................................... 56
2.5.6 Household Size ................................................................................................................................................... 56
2.5.7 Single Family Residences ............................................................................................................................... 56
2.6 Conclusion ............................................................................................................................................................... 58
Section 3.0 Analysis Of Existing Economic Base ................................................................................................ 60
3.1 Introduction To Escambia’s Economy: ............................................................................................................. 60
3.2 Economic Base Theory:........................................................................................................................................... 61
3.3 Specialization Analysis ............................................................................................................................................ 61
3.3.1 Introduction ........................................................................................................................................................ 61
3.3.2 Healthcare:........................................................................................................................................................... 63
3.3.3 Federal Government ........................................................................................................................................ 65
3.3.4 Retail And Accommodations ........................................................................................................................ 65
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3.3.5 Local Government: ........................................................................................................................................... 66
3.4 Concentration Analysis ........................................................................................................................................... 66
3.5 Location Quotient Analysis ................................................................................................................................... 69
3.6 Industry Trends ......................................................................................................................................................... 71
Conclusion ........................................................................................................................................................................... 74
Section 4.0: Analysis Of Future Population .......................................................................................................... 76
4.1 The Forecast Scenario: ............................................................................................................................................ 76
4.1.1 Factors Promoting Growth ........................................................................................................................... 76
4.1.2 Factors Hindering Growth ............................................................................................................................ 78
4.1.3 Qualitative Influence On Forecast: ............................................................................................................ 81
4.2 Results From The Projection Techniques ....................................................................................................... 82
4.2.1 Extrapolation Technique ............................................................................................................................... 82
4.2.2 Ratio Techniques............................................................................................................................................... 85
4.3 Final Population Forecast ...................................................................................................................................... 86
5.0 Conclusion ......................................................................................................................................................................... 90
Appendix A: Methodological Details On Population And Economic Analyses .................................. 93
A.1 Data Sources ................................................................................................................................................................ 93
A.2 Specialization Analysis ........................................................................................................................................... 93
A.3 Concentration Analysis ........................................................................................................................................... 93
A.4 Location Quotient (Lq) ........................................................................................................................................... 94
Appendix B: Population Projections Technical Appendix ........................................................................... 97
B-1 Extrapolation Technique ....................................................................................................................................... 97
B.1.1 Extrapolation Technique Introduction:................................................................................................... 97
B.1.2 Input Evaluation Procedures .................................................................................................................... 101
B.1.3 Output Evaluation Procedures:................................................................................................................ 101
B.1.4 Crv, Me, And Mape Findings ...................................................................................................................... 103
B-2 Ratio Technique ..................................................................................................................................................... 105
B.2.1 Ratio Technique Introduction .................................................................................................................. 105
B.2.2 Constant-Share Ratio Method .................................................................................................................. 105
B.2.3 Shift-Share Ratio Method ........................................................................................................................... 106
B.2. 4 Share Of Growth Method: .......................................................................................................................... 106
B.2.5 Group Quarter Consideration ................................................................................................................... 108
B.2.6 Comparison To Florida ................................................................................................................................ 110
B-3 Population Forecast.............................................................................................................................................. 110
References ............................................................................................................................................................................. 112
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List Of Maps, Tables, And Figures
Map 1.1: Forecast Study Region ......................................................................................................... 11
Map 1.2: Escambia Census Places ...................................................................................................... 15
Map 1.3: Conservation Lands In Escambia County............................................................................ 18
Map 1.4: Infrastructure In Escambia County ..................................................................................... 20
Map 1.5: Poverty And School Quality, 2010 ...................................................................................... 26
Map 2.1: Regional Percent Change In Population, 2000 – 2010 (U.S. Census 2010) ...................... 34
Map 2.2: Census Tract Population Growth Rates, 2000 - 2010 ........................................................ 38
Map 2.3: Census Tract Population Growth Rates, 2000 - 2010 ........................................................ 50
Map 4.1: Census Block Group Population Growth Rates, 2000-2010 .............................................. 80
Table 1.1: Cities Over 150,000 Within A 200-Mile Radius Of Escambia County, Florida ................ 10
Table 1.2: Escambia County Water Treatment Facility Capacity, 2010 ............................................ 23
Table 1.3: Escambia County Wastewater Flow Projections 2015-2035 ........................................... 23
Table 2.1: Population Growth And Net Change In Region, 1990-2010 ............................................ 36
Table 2.2: Group Quarters Population In Escambia County ............................................................. 45
Table 2.3: Socioeconomic Indicators In Escambia, Neighboring Counties, And Florida .................. 46
Table 2.4: Growth Rate And Unemployment Rate Comparison For Escambia, Region, And Florida
(1990 – 2010) ...................................................................................................................................... 48
Table 2.5: Escambia County Housing Data (2005 – 2012) ................................................................ 51
Table 2.6: Percent Change Of Number Of Housing Units In Escambia Region, 1990-2010 ............ 53
Table 2.7: Vacancy Rates In Region And State, 2008-2012 ............................................................... 54
Table 2.8: Escambia Region Households: Percentage Family Households, 1990-2010 ................. 56
Table 2.9: Escambia Region Household Size, 2000-2010 .................................................................. 57
Table 2.10: Percentage Single Family Residences, 2000-2010 ......................................................... 57
Table 3.1: Net Job Growth Rates ........................................................................................................ 61
Table 3.3 Major Employers In Escambia County, 2013 ..................................................................... 65
Table 3.3: Share Of County Workforce Working In Escambia County .............................................. 68
Table 4.1: County Population Best Projections, 2010-2030, Using The Extrapolation Technique . 82
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Table 4.2: Escambia County Population Forecast 2020-2040 .......................................................... 88
Table B.1: Group Quarter Population In Escambia, Fl ....................................................................... 98
Table B.2: Evaluation Of Extrapolation Curves ................................................................................103
Table B.3: Bebr Projections For The Wfrpc ......................................................................................105
Table B.5: Escambia County Shift-Share Projections .......................................................................106
Table B-6: Escambia County Population And Projections (In Blue) Using Ratio Methods ............107
Table B-7: Best-Fitting Population Projection Curves For Escambia ..............................................110
Table B-8: Fine Adjustments To Projection Values For Final Forecasting ......................................111
Figure 2.1: Escambia Population From 1960 – 2010 (U.S. Decennial Census) ................................ 31
Figure 2.2: Region Population From 1960 – 2010 (U.S. Decennial Census) .................................... 31
Figure 2.3: Florida Population From 1960 – 2010 (U.S. Decennial Census) ..................................... 32
Figure 2.4: Population Growth Rate For Escambia, Region, And State, 1970 – 2010 (U.S.
Decennial Census) ............................................................................................................................... 33
Figure 2.5: Share Of Regional Growth For Escambia, Baldwin, And Santa Rosa, 1970-2010 (U.S.
Decennial Census) .............................................................................................................................. 35
Figure 2.7: Percent Of Total Population Living Inside Urban Areas (1990-2010) ............................ 39
Figure 2.8: Escambia County Population Pyramid, 2010 .................................................................. 41
Figure 2.9: Ethnic Distribution In Escambia County, Its Region, And Florida ................................... 42
Figure 2.10: Ethnic Distribution In Escambia County, Its Region, And Florida ................................. 43
Figure 2.11: Percent Unemployment Rate For Escambia County, Region Median, And Florida
(1990 – 2000) ...................................................................................................................................... 47
Figure 2.12: Violent Crimes Per 100,000 People ............................................................................... 49
Figure 2.13: Regional Increase In Occupied Housing ........................................................................ 54
Figure 2.14: Florida And Escambia Region Housing Values, 1990-2010 .......................................... 55
Table 3.2: Number Of Jobs In Naics Industries In Different Regions (2011) .................................... 62
Figure 3.1: Specialization Analysis ...................................................................................................... 64
Figure 3.2: Regional Concentration Analysis ...................................................................................... 67
Figure 3.3: Escambia County Industry Location Quotients 2011 ...................................................... 70
Figure 3.4: Key Sectors Net Job Growth Rates, 2006-2011 .............................................................. 72
Figure 3.5: Promising Sectors Net Job Growth Rates, 2006-2011 .................................................... 73
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Figure 4.1: Escambia Population Projections Excluding Group Quarters, 2010-2030 Best Curve
Types Base Period 1960-2010 ............................................................................................................ 83
Figure 4.2: Escambia Population Projections, 2010-2030 ................................................................. 84
Figure 4.3: Best Projections Using The Ratio Technique ................................................................... 86
Figure 4.4: Escambia County Population Forecast, 2010 – 2040 ..................................................... 87
Figure B.1: Group Quarters Composition, 2000-2010 ...................................................................... 99
Figure B.2: Non-Group Quarter Projections, 2010-2030 ................................................................100
Figure B.3: County Projections, 2010-2030 .....................................................................................100
Figure B.4: Non-Group Quarter Projections, 2010-2030 ................................................................104
Figure B.5: Escambia County Projections, 2010-2030 .....................................................................104
Figure B-5: Projection Results From Three Ratio Techniques .........................................................107
Figure: B.6: Ratio Techniques Holding Group Quarter Population Constant .................................109
Figure B.7: Ratio Technique With Florida.........................................................................................109
B A C K G R O U N D &
C O N T E X T
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1.0 BACKGROUND & CONTEXT
1.1. GEOGRAPHY
Escambia is the westernmost county in the state of Florida and is part of the Pensacola-
Ferry Pass-Brent Metropolitan Area. Its total land area is 656.46 square miles with the Escambia
River bordering to the west, the Perdido River to the East, and the Gulf of Mexico to the South.
Furthermore, the county includes most of the Perdido Key and half of Santa Rosa Island, both
being barrier islands in the Gulf of Mexico. The county shares borders with Escambia County,
Alabama, on the north; Santa Rosa County, Florida, on the east; and Baldwin County, Alabama,
on the west. Escambia’s location makes it closer to Alabama and Mississippi than much of the
state of Florida. As Table 1.1 shows, Tallahassee is the only major city in Florida within a 200-mile
radius from the county, the rest being from other states.
TABLE 1.1: CITIES OVER 150,000 WITHIN A 200-MILE RADIUS OF ESCAMBIA COUNTY, FLORIDA
For analyzing the growth in Escambia County, Beards and Associates (B&A) define the
Escambia Region as consisting of the following counties: Escambia County, Florida; Okaloosa
County, Florida; Santa Rosa, Florida; Baldwin County, Alabama; Escambia County, Alabama; and
Mobile County, Alabama (see Map 1.1). These counties represent the Escambia Region due to
their physical proximity and economic ties. For the remainder of this document any reference of
“region” will be referring to these six counties. Moreover, any reference made to Escambia
County will refer to Escambia County, Florida, rather than Escambia County, Alabama.
ESCAMBIA
COUNTY SANTA ROSA
COUNTY BALDWIN
COUNTY
MOBILE
COUNTY
OKALOOSA
COUNTY
ESCAMBIA
COUNTY
MOBILE
BAY
N
ALA
BA
MA
ALABAMA
FLORIDA
MAP 1.1: FORECAST STUDY REGION
0 5 30 Miles
2010 CENSUS POPULATION DENSITY: 1 DOT = 200 PEOPLE
ESCAMBIA COUNTY
PENSACOLA METRO AREA
STUDY REGION
STATE BOUNDARIES
INTERSTATE
MAJOR ROADS
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1.2 HISTORY
Before European contact, what is now Escambia County had been host to various peoples
for at least 12,000 years, the last of them being the Creek and Choctaw Indian tribes (Annenberg
Foundation, 2014). In August 1559, Spanish explorer Tristán de Luna established the oldest
European settlement in the United States on the coast of Pensacola Bay. The name Pensacola
comes from Panzacola, a name given to the region by a local tribe, which may mean “long-haired
people,” after indigenous inhabitants (Webster, 2009). The colony faced numerous setbacks
caused by hurricanes and lack of supplies and, by fall of 1561, the only remaining military
outpost was deserted (Webster, 2009). Wary of the French presence in New Orleans, the
Spanish established yet another garrison in 1698, and began to lay out the colonial town that
would become Escambia County’s capital. Starting in 1719, the city switched hands between the
Spaniards, French and British, ending back in Spanish hands but then ceded to the United States
in 1821. Half a century later, during the Civil War, the confederates occupied the city along with
the rest of Florida. Given this tumultuous history, Pensacola is known as the city of five flags
(Webster, 2009).
When Florida became an American Territory in 1821, it was divided into two very large
counties, with the Suwannee River as the divider. Escambia County encompassed all the Florida
territories to the west and St. John County everything to the east. Since each county was
subsequently divided into others, both Escambia and St. John shrank in size over the years
(Parker, 2008).
Compelled by the harbor and the vast amount of lumber in the area, President Adams
commanded in 1825 to build a Navy shipyard in Pensacola. One year later a Navy hospital further
expanded the facilities, bringing jobs and infrastructure to the area. In 1914, with an increasing
demand for aviation, the shipyard was repurposed as the Naval Air Station Pensacola, the Navy’s
first air station and flight school. Since WWII the scale of naval operations has increased even
further, and Pensacola remains an important asset for the U.S Navy (FDS, 2014).
Healthcare has historically been an important part of Escambia’s history and economy.
One of the first ordinances that were enacted by Territorial Governor Andrew Jackson was the
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establishment of a health board and quarantine station in Pensacola in 1821 to help control
yellow fever. In addition, a U.S. Marine Hospital was constructed in 1854, and in 1953, an
Escambia Board of County commissioners passed an ordinance that established the health
department as a continuing county function, and has subsequently grown and expanded its
services in Pensacola and Century (Lanza, 2014).
1.3 KEY PLACES
1.3.1 MUNICIPALITIES
Besides the city of Pensacola, the one and only other municipality in Escambia County is
the town of Century. After noticing during the last decade of the 19th century successful
enterprises in the forests of South Georgia, Martin Sullivan and Russell A. Alger decided to form
the Alger-Sullivan Lumber Company in present-day Century, whose name commemorates its
creation at the turn of the century. Though the company shut down in 1957, the community of
Century maintained residents and in 1980 incorporated as the Town of Century.
1.3.2 CENSUS DESIGNATED PLACES
There are a total of ten Census Designated Places in the county, most of which are in the
southeastern part of Escambia, close to Pensacola. These are Bellview, Brent, Ensley, Ferry Pass,
Gonzalez, Goulding, Molino, Myrtle Grove, Warrington, and West Pensacola (see Map 1.2).
1.3.3 MILITARY PRESENCE
As mentioned above, Escambia County is home to the Naval Air Station Pensacola (NASP),
known as “The Cradle of Naval Aviation” for its role as the first US Navy operating air station and
flight school. This has been a major training site for thousands of naval aviators including the Neil
Armstrong, the first man to walk on the moon.
Besides serving as a training site, the NASP has an educational branch called the National
Flight Academy that brings 12,000 middle and high school students to the area on a yearly basis.
Indeed, the US military has a powerful presence in the region. With an annual economic impact
of $6.7 billion, it supports over 66,700 jobs in the county (Haas, 2013). Cutting-edge scientific
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research has likewise been spurred by the military: the Florida Institute for Human and Machine
Cognition (IHMC) is a public non-profit research institute that specializes in robotics, artificial
intelligence, human-machine interaction, cognitive psychology, and science. They have an
impressive list of clients that includes NASA, Boeing, Microsoft, Honda, and a vast array of US
military offices.
1.3.4. MANUFACTURING
The manufacturing sector has a moderate but important presence in Escambia County.
Even though the old Alger-Sullivan Paper Mill closed its doors, International Paper (IP)—the
largest pulp and paper company in the world—has a corporate office and industrial packaging
center approximately 10 miles north of Pensacola. GE Energy is likewise another important
player in the region. Located in Pensacola, this energy plant assembles wind turbines and has
delivered more than 8,000 units since it was created in 2002. Ascend Performance Materials,
located west of Pensacola, is another important manufacturer that produces nylon, plastics, and
synthetic fibers.
1.3.5 HEALTHCARE
Escambia County’s healthcare sector employs more than 10,000 people and includes
prominent centers such as the Andrews Institute for Orthopedics and Sports Medicine, a well-
renowned facility that serves primarily athletes; the Sacred Heart Health System, an old yet
vibrant center opened in 1915; the West Florida Healthcare; and the Navy Hospital. All five
facilities are located south of I-10.
1.3.6 PRISON
The Escambia County Jail is the only jail in the county, residing in south-central Pensacola.
It provides about 450 jobs to the county and holds about 1,600 inmates. As it will be later
discussed, this inmate population has a slight impact in Escambia County’s demographics.
N
ESCAMBIA
COUNTY
SANTA ROSA
COUNTY BALDWIN
COUNTY
MAP 1.2: ESCAMBIA CENSUS PLACES
0 5 10 Miles
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1.3.7 HIGHER EDUCATION
The county boasts several colleges and universities, including the Embry-Riddle
Aeronautical University, the University of West Florida, the Florida State University College of
Medicine, the Pensacola State College, the Pensacola Christian College, and a campus of the
Alabama-based Troy University. The University of West Florida is the largest with 12,000
students and 1,231 employees. Escambia County also hosts one junior college, Pensacola Junior
College, and two technical schools, George Stone Vocational Training Center and West Florida
Technical High School.
1.4 NATURAL RESOURCES
Escambia County enjoys a variety of natural resources and conservation lands. Its interior
land is comprised of tree farms, agricultural lands and numerous forest types such as baygall,
upland hardwoods, xeric hammock, and upland pine. The county is home to several rare species:
thirty species of rare plants and lichens, eighty-three rare vertebrates, and seventy-eight rare
invertebrates. A few examples of these include the gulf sturgeon, white-top pitcher plant,
eastern indigo snake and the gopher tortoise. (Florida Natural Areas Inventory FNAI December
2013 fnai.org)
1.4.1 GROUNDWATER:
Escambia County does not have access to the Floridan aquifer that many other counties
in the Florida Great Northwest have. Instead, it relies on a shallower sand-and-gravel aquifer
system that depends on local rainfall to recharge. An average of nearly sixty inches of rain per
year in Escambia County sustains this aquifer system. (University of Florida Institute of food and
agricultural services -escambia.ifas.ufl.edu)
1.4.2 SURFACE WATER
The Pensacola Bay system is the largest body of water in the county and the fourth
largest bay system in Florida. It comprises a series of bays and lagoons shared between Florida
and Alabama. The watershed covers nearly 7,000 square miles between the two states.
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Additionally, it has a strategic importance as it provides navigable waters for military and
commercial use. Pensacola Bay is part of the Northwest Florida Water Management District,
which manages the watershed. (Northwest Florida water management district
nwfwmd.state.fl.us/recreation/escambiariver.html)
The Escambia River flows south into the bay system for about fifty-four miles, thirty of
which are a protected forested river corridor. This protection is critical for filtration and runoff
control into the river system. The river also contains eighty-five native freshwater species.
1.4.3 CONSERVATION LANDS
The county contains twenty-four conservation lands that are owned or maintained by
state, federal, and private organizations and cover an area of 80,912 acres, or 19% of Escambia’s
land area. Much of this land is located along the Escambia River corridor, and farther to the
south, coastal areas alongside the bay systems (see Map 1.3). Most notable of these
conservation lands is Gulf Islands National Seashore, which is the largest tract of protected
seashore in the United States (fnai.org/gisdata.cfm).
N
ESCAMBIA
COUNTY
SANTA ROSA
COUNTY BALDWIN
COUNTY
MAP 1.3: CONSERVATION LANDS IN
ESCAMBIA COUNTY
0 5 10 Miles
LAND IN CONSERVATION
ESCAMBIA COUNTY BORDER
OTHER COUNTY BORDERS
Florida Natural Areas Inventory, March 2014
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PARKS
There are eighty-six local parks within Escambia County, three state parks, and one national
seashore. Many of the smaller parks are in the City of Pensacola and most of larger parks are
located within the various conservation lands in the county. Notable parks include the Gulf
Islands National Seashore, Big Lagoon State Park, and Tarkiln Bayou State Park.
AGRICULTURAL LAND
Agricultural land makes up a significant portion of the total area of Escambia County:
there are 142 parcels that make up 189,423 acres of land classified as agricultural, accounting for
45% of Escambia’s total land area. Much of this land use type is located in the northern regions
of the county, its southern part being either urban or for conservation. Escambia’s agricultural
types range from coniferous tree farms to peanut and cotton farms. (Cathy Andrews, Escambia
County GIS myescambia.com/business/ds/gis cjc)
1.5 INFRASTRUCTURE
Infrastructure plays a vital role in the quality of life for a county’s residents and its condition
has the potential to either encourage or limit population growth. Below is an account of the current
state of Escambia County’s infrastructure.
1.5.1 MAJOR ROADS
As shown in Map 1.4, Escambia County hosts two federal interstates, Interstate 10 and
Interstate 110, as well as three federal highways, US-29, US-90, and US-98. I-10 provides an east
to west route within southern Escambia. I-10’s vast two-thousand-mile expanse, from
Jacksonville, Florida, to Santa Monica, California, provides Escambia with a direct connection
with other counties and states adjacent to the highway.
N
ESCAMBIA
COUNTY
SANTA ROSA
COUNTY BALDWIN
COUNTY
MAP 1.4: INFRASTRUCTURE IN
ESCAMBIA COUNTY
0 5 10 Miles
ESCAMBIA COUNTY
PENSACOLA METRO AREA
NAVY AIR STATION PENSACOLA
INTERSTATE 10
MAJOR ROADS
RAILROAD
ESCAMBIA INTERNATIONAL AIRPORT
PORT OF PENSACOLA
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1.5.2 BRIDGES
Due to Escambia’s coastal location, the county is home to an abundance of bridges, most
of them being located within Pensacola. Three bridges connect Escambia County to its eastern
neighbor, Santa Rosa County: the Escambia Bay Bridge, the Pensacola Bridge, and the Escambia
River Bridge. The bridges with the highest traffic rates are The Escambia Bay Bridge and the
Pensacola Bay Bridge. The Escambia Bay Bridge is a portion of I-10, consisting of two, 2.6 mile
long, three lane, bridges which are designated for eastbound and westbound traffic. The bridges
cross the Escambia Bay and connect Escambia County to Santa Rosa County. The bridge has a
grade B peak level of service. Traffic rates are highest in the morning and the evening as people
travel across the bridge to go to and from Pensacola.
The Pensacola Bay Bridge also connects Escambia to Santa Rosa, this time crossing the
Pensacola Bay south of Pensacola; it has four lanes and its traffic flows north and southbound for
three miles. The bridge has been deemed structurally deficient and so the Florida Department of
Transportation (FDOT) is planning the construction for a replacement bridge. Construction is
expected to begin within the next three to five years.
1.5.3 RAIL ROADS/PORT OF PENSACOLA
Escambia County has two major railways, the CSX Rail and Alabama Gulf Coast Shoreline,
both of which provide freight transportation and encourage trade. Entering parallel to the
Escambia Bay Bridge, the CSX tracks then follow the county’s southeast border before heading
north to Alabama. The Alabama Gulf Coast Shoreline railroad travels north to south through
Escambia on the west edge of the county. It is no coincidence the CSX Rail tracks travel as far
south as The Port of Pensacola. The Port of Pensacola is the leading deep-water port in
Northwest Florida. The port’s eight deep-draft berths and fifty facility acres provide access to
international waters and transportation services commodities that are utilized throughout the
country.
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1.5.4 AIRPORT
The Pensacola International Airport is located in Northeast Pensacola, in close proximity
to both I-10 and I-110. The airport typically has eighty arrivals and departures per day, allowing
for about 1.5 million passengers to travel through the airport each year (Transportation). The
airlines connecting to Pensacola International Airport include Delta, Silver Airways, American
Airlines, Southwest Airlines, United, and US Airways. Direct flights are offered to: Orlando,
Tampa, Miami, Houston, Dallas, Atlanta, Nashville, Charlotte, Washington D.C, and Chicago.
1.5.5 WASTEWATER TREATMENT FACILITIES
Escambia County’s two major water and sewer providers are Emerald Coast Utilities
Authority (ECUA) and Peoples Water Service Company. The People’s Water Service Company
provides water service but not sewer. The ECUA provides both water service and sewer services
operating three wastewater treatment plants: the Central Water Reclamation Facility (formerly
ECUA Main Street), the Bayou Marcus Water Reclamation Facility, and the Pensacola Beach
Wastewater Treatment Plant.The Town of Century owns Escambia’s final wastewater treatment
facility which is appropriately called the Town of Century Wastewater Treatment Facility.
In 2010, Escambia County was well under its water treatment capacity. Table 1.2 shows
the total wastewater flow for each water treatment facility. Not a single facility has reached its
capacity (Northwest Florida Water Management District). With a total wastewater treatment
facility capacity of 31.05 mgd, Escambia County had an available capacity of 6.68 mpd in 2010.
Based off the Bureau of Economic and Business Research’s population forecast, the Northwest
Florida Management District does not expect Escambia County to go over its wastewater
treatment facility capacity by 2035.
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TABLE 1.2: ESCAMBIA COUNTY WATER TREATMENT FACILITY CAPACITY, 2010
Source: Northwest Florida Water Management District, 2013 Water Supply Assessment
In contrast, the Northwest Florida Management District projects that the 2035 total
wastewater flow will decrease to 23.59 mgd. Researchers at Northwest Florida Management
District found that wastewater use decreased post 2010 and they believe that the decline was a
result of the economic recession and a conscious effort made by Escambia County citizens to use
less water . The Northwest Florida Management District took this information into account when
projecting water flow in 2015 and beyond, which results in a decreased wastewater flow in by
2035. As a result, in 2035, Escambia County is expected to have an available capacity of 7.46
mgd. Escambia County’s wastewater flow projections from 2015-2035 are demonstrated in Table
1.3.
TABLE 1.3: ESCAMBIA COUNTY WASTEWATER FLOW PROJECTIONS 2015-2035 (MILLIONS OF GALLONS PER DAY)
Source: Northwest Florida Water Management District, 2013 Water Supply Assessment
Faci l i ty Name
Plant
Capacity
Total
Waste-
water Flow
Reuse
Capacity Reuse Flow
Bayou Marcus WRF 8.2 6.51 0 0
ESCA-Main Street 20 16.45 7 1.13
Pensacola Beach WWTP 2.4 0.96 0.43 0.05
Town of Century WWTF 0.45 0.46 0 0
Escambia County Total 31.05 24.37 7.43 1.18
Estimated
Water Use Category 2010 2015 2020 2025 2030 2035
Public Supply 39.55 40.13 40.85 41.48 42.04 43.51
Domestic self-supply 1.46 1.46 1.48 1.5 1.51 1.52
Ind/Comm/Inst. 32.3 28.91 28.07 27.08 27.09 27.1
Recreational self-supply 3.69 3.74 3.81 3.86 3.91 3.96
Power generation 2.57 3.32 3.32 3.32 3.32 3.32
15.91 15.91 17.59 17.59 17.59 17.59
Total 95.38 93.48 95.11 94.83 95.46 95.99
Projected
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1.5.5 POTABLE WATER
Escambia County is part of the Northwest Florida Management District, one of Florida’s
five water management districts. It serves Bay, Calhoun, Escambia, Franklin, Gadsden, Gulf,
Holmes, Jackson, Leon, Liberty, Okaloosa, Santa Rosa, Wakulla, Walton, Washington and western
Jefferson County. Groundwater supplies the majority of Escambia’s freshwater supply. As
discussed in section 1.4, the primary source of groundwater is the Sand and Gravel Aquifer.
Currently, Escambia County has thirty-two wells, twenty-eight of them being currently operating.
The Northwest Florida Water Management District estimated that in 2010, approximately 80.46
million gallons of water per day (mg/d) of water was withdrawn from the sand-and-gravel
aquifer. This represents forty-eight percent of Escambia County’s water budget.
The Northwest Florida Water Management District considers Escambia’s potable
resources, “adequate to meet the projected 2035 average and 1-in-10 year drought event
demands, while sustaining water resources and related natural systems” (Northwest Florida
Water Management District, 2014, p.3-13). This is because current projections indicate that
water demand for Escambia County will increase by less than one percent by 2035 and that
rainfall will be able to provide adequate aquifer recharge for Escambia County. However, the
county must be careful to monitor localized areas where withdrawals are concentrated,
particularly in periods of drought. Most of the withdrawal concentrations are located in southern
Escambia.
1.5.6 PARKS (86 COUNTY PARKS)
Escambia County is home to dozens of parks and community centers. The two largest
parks, Big Lagoon State Park and Perdido Key State Park, are both located in southwest
Escambia. The Perdido Key Barrier Island, the latter being home to the Perdido Key State Park,
separates big Lagoon State Park from the Gulf of Mexico.
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1.5.7 PUBLIC TRANSIT
The County is able to provide public transit services via the Escambia County Area Transit
(ECAT). The ECAT offers more than 1,500 bus and 285 miles of routes and its primary mode of
transit is the bus. However, the ECAT also provides a seasonal Pensacola Trolley and a campus
trolley to the University of West Florida (UWF). In 2012, the ECAT had a record 1.6 million annual
passenger trips.
1.5.8 PUBLIC EDUCATION
Escambia County is particularly disadvantaged in public education (see map 1.4). As noted
by the Florida Department of Education, Escambia County’s school district grade has fluctuated
between grade B and grade C since 2004 (Florida School Grades, 2013). In 2010, with a school
district grade of C, Escambia County ranked in the bottom twenty-five percent of Florida’s school
districts and in the bottom twenty percent of Florida’s Great Northwest’s school districts.
Escambia’s closest neighboring Florida counties, Santa Rosa, Okaloosa, and Walton, outperform
Escambia County in school quality, having district grades of A compared to Escambia’s grade of C
(Florida School Grades, 2013).
Though not dramatically different, neighboring Baldwin County also outperforms
Escambia in school quality with a grade of B. Mobile and Escambia, Alabama, are the only two
counties in the region against which Escambia has a better grade. On the opposite side of the
spectrum is Santa Rosa. This county not only received a school district grade of A but it is also the
second ranked school district within the state of Florida (Florida School Grades, 2013). Santa
Rosa has consistently ranked in the top ten Florida school districts throughout the last decade.
This is in stark contrast to Escambia County, which falls within the poorest twenty-five percent of
Florida’s school District.
Given the significance that public schools have in either attracting or repelling residential
growth, this aspect can be an important shaper of the county’s future growth. The discrepancy
between Escambia and Santa Rosa will likely encourage families searching for quality education
to settle in the latter rather than the former.
N
ESCAMBIA
COUNTY SANTA ROSA
COUNTY
BALDWIN
COUNTY MOBILE
COUNTY
OKALOOSA
COUNTY
ESCAMBIA
COUNTY
MOBILE
BAY
MAP 1.5: POVERTY AND SCHOOL QUALITY
D B
C
D
A A
7 – 8%
9 – 10%
11 – 13%
15 – 20%
FAMILIES:
INCOME IN 2010
BELOW POVERTY
LEVEL
ACS 2006 – 2010 (5-Year Estimates)
1 dot = 100 people
CONCENTRATION OF FAMILIES
INCOME IN 2010 BELOW
POVERTY LEVEL
ACS 2006 – 2010 (5-Year Estimates)
ESTIMATED
SCHOOL
GRADE
A Good
B Moderate
C Low Performing
D Poor
F Failing
Florida Department of Education,
Florida School Grades
Greatschools.org/alabama
27 | P a g e
1.6 ECONOMIC TRENDS
The Haas Center, an independent research group of the University of West Florida,
estimates that Naval and defense industry generates 45% of the Escambia County Gross Regional
Product at just over $6.7 Billion (see also section 1.3). This strong military presence employs
directly or indirectly over 66,700 people countywide and provides $340 Million in combined
salaries. Additionally, numerous high-tech companies specializing in aerospace and robotics
have sprouted, fueled by defense procurement funds. Of the 17 largest employers for the
Pensacola Metropolitan Area, the top three relate to government services either at a local, state,
or federal level (Haas, 2013).
With efforts such as Vision 2015 and support from a “business-friendly” state governor,
the hope for the Pensacola Metropolitan Area is to attract new business to the region and
augment opportunities for current employers to expand. Vision 2015 is a five-year plan for job
creation that aimed in 2010 for 3,000 additional jobs in the region. With the expansion of Navy
Federal Credit Union, the high-tech company CTS America, and the addition of two major
international employers, iGATE Outsourcing Company and West Fraser Forestry Company; this
goal was accomplished two-years ahead of schedule.
Outside of these efforts to promote commercial growth, however, challenges loom in
Escambia County, where unemployment continues to plague opportunity for many of its
residents. The U.S. Census reports that the share of people in Escambia living below poverty level
between 2008-2012 is higher than the Florida average (17.8% and 15.6% respectively) and its
median household income lower than the Florida average ($43,806 and $47,309 respectively).
While the military is a major industry for in Escambia County, its growth in the past years
has been moderate. Furthermore, healthcare and tourism, two sectors that have been
historically the drivers of the county’s economy, have been in decline. The education industry is
the only one that has been growing in a robust manner and there may lay Escambia’s future.
Section 3 will cover in much greater detail the economic composition and industry trends in the
county.
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1.7 MAJOR ATTRIBUTES
To sum, these are the major attributes in the county:
● The county enjoys a strategic location with a major port. With the two interstate
highways and water treatment plants projected to have capacity by 2035, the county’s
infrastructure is adequate to meet future demands.
● The military presence and the healthcare sector are major sectors in Escambia’s
economy. However, neither of them shows signs of robust growth.
● Escambia County has challenges with its public school education, which is considered
worse than its neighbors and the state of Florida.
● Even though the county is an employment hub in the region, it has a higher
unemployment rate and lower median household income than the rest of the state.
A N A L Y S I S O F C U R R E N T
P O P U L A T I O N
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2.0 ANALYSIS OF CURRENT POPULATION
This section provides an overview of the current population and demographic trends in
Escambia County. It is essential for population forecast to look at historical population trends in
order to see how the county is changing through time.
We first look at changes in the number of people living in Escambia County and the
surrounding region. We then analyze the demographic characteristics of the population in order
to have a better understanding of the local context. We examine race, group quarters
population, education, crime rate and educational attainment looking for factors that might have
an impact on population growth.
2.1 POPULATION
2.1.1 POPULATION BY DECADE FOR ESCAMBIA, REGION, AND STATE
Figure 2.1 shows the population in Escambia County for every decennial census since
1960. While the pace of growth was steady from 1960 to 2000, it
came to an abrupt halt between 2000 and 2010. Even though the
Great Recession took place at the end of that decade, Figures 2.2 and
Figures 2.3 evidence that, the halt in Escambia is inherent to the
county itself rather than the region or state. In fact, all three Figures
look strikingly similar in their linear population trend: since 1970,
Florida has added roughly three million people, the Region 130,000, and Escambia about
30,000—except during the last decade when it only added a little over 3,000 (!).
Population
growth comes
to an abrupt
halt between
2000 and 2010
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FIGURE 2.1: ESCAMBIA POPULATION FROM 1960 – 2010
(U.S. DECENNIAL CENSUS)
FIGURE 2.2: REGION POPULATION FROM 1960 – 2010 (U.S. DECENNIAL CENSUS)
297,619 294,410
262,798
233,794
205,334 173,829
50,000
100,000
150,000
200,000
250,000
300,000
350,000
1960 1970 1980 1990 2000 2010
Po
pu
lati
on
Year
1,263,389
1,161,349
1,000,623
881,678
742,858
661,451
200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,000
1960 1970 1980 1990 2000 2010
Po
pu
lati
on
Year
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FIGURE 2.3: FLORIDA POPULATION FROM 1960 – 2010 (U.S. DECENNIAL CENSUS)
2.1.2 GROWTH RATE FOR ESCAMBIA, REGION, AND STATE
All three geographical areas have seen a decline in their growth rate for the last three
decades (see Figure 2.4). The growth rate of Florida has always been higher than that of
Escambia and its region. However, while Escambia had a greater rate than its region before
1980, the region outpaced our county from 1980 and onwards. Yet again, the sudden drop from
12% to 1% for the county’s growth rate is certainly much more dramatic than the drop from 16
to 9% for the region, and from 24% to 18% for the state. This difference suggests that the factors
that affect Escambia’s growth are likely different from those that affect the state or the region.
18,801,310
15,982,378
12,937,926
9,746,324
6,789,443
4,951,560
-
2,000,000
4,000,000
6,000,000
8,000,000
10,000,000
12,000,000
14,000,000
16,000,000
18,000,000
20,000,000
1960 1970 1980 1990 2000 2010
Po
pu
lati
on
Year
33 | P a g e
FIGURE 2.4: POPULATION GROWTH RATE FOR ESCAMBIA, REGION, AND STATE,
1970 – 2010 (U.S. DECENNIAL CENSUS)
Map 2.1 shows that between 2000 and 2010 Escambia County was the slowest-growing
county in the region after Escambia, Alabama. Moreover, the Map shows that the geographical
concentration of growth in the region is happening in the counties immediately east and west of
Escambia, namely Santa Rosa, FL, and Baldwin, AL.
Once a major growth generator, Escambia
accounted for nearly forty percent of the region’s
growth in 1970 while its two neighboring counties
accounted only for a little over ten percent (see
Figure 2.5). Now the roles have quite reversed in the
present: while Escambia contributed to 3.14% of the
regional growth in 2010, Santa Rosa and Baldwin
added 33% and 41%, respectively.
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
1970 1980 1990 2000 2010
Gro
wth
rat
e
Year
Escambia
Region
Florida
Escambia accounted for
nearly forty percent of the
region’s growth in 1970
while its two neighboring
counties accounted only for
a little over ten percent.
Now the roles have reversed.
N
ESCAMBIA
COUNTY
SANTA ROSA
COUNTY
BALDWIN
COUNTY
MOBILE
COUNTY
OKALOOSA
COUNTY
ESCAMBIA
COUNTY
MOBILE
BAY
MAP 2.1: REGIONAL PERCENT CHANGE IN POPULATION
0 5 30 Miles
-0.3% DECLINE
1 – 2% GROWTH
3 – 4% GROWTH
6 – 7% GROWTH
28 – 30% GROWTH
PERCENT
CHANGE IN
POPULATION,
2000-2010
Census 2010 (redistricting Data – PL94)
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FIGURE 2.5: SHARE OF REGIONAL GROWTH FOR ESCAMBIA, BALDWIN, AND SANTA ROSA, 1970-2010 (U.S. DECENNIAL CENSUS)
2.1.3 GROWTH RATES BY YEAR FOR ESCAMBIA AND REGION, 2000-2010
In order to better understand Escambia’s slowing growth rate in the 2000s, it is helpful to
take a closer look at the decade 2000-2010. The first assumption one might make is that its
growth decline is due to the economic recession of 2008. However, as demonstrated in Figure
2.6, Escambia’s growth rate slowed well before that year: the county experienced negative
growth rates as early as 2001-2002. Furthermore, its neighboring counties in the region
continued to experience significant population growth. Indeed, most of them experienced
growth rates higher than six percent. Baldwin and Santa Rosa grew almost exponentially, with
rates of 29% and 28%, respectively. Since the economic recession did not prevent other counties
from growing, and since Escambia showed poor growth rates from the beginning of the decade,
we can safely say that the economic recession of 2008 is not solely responsible for the lack of
growth in Escambia. This reinforces the idea that the reasons for Escambia’s growth decline must
be inherent to Escambia as opposed to being part of a regional, state, or national trend.
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
1970 1980 1990 2000 2010
Shar
e o
f R
egio
nal
Gro
wth
Year
Escambia
Santa Rosa
Baldwin
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2.1.4 POPULATION GROWTH OUTLIERS IN THE REGION
As can be seen in Table 2.1 both Santa Rosa County and Baldwin County had population
booms in the 90s, Santa Rosa with a growth rate of forty-four percent and Baldwin with a growth
rate of forty-two percent. During this same time,
Escambia County had a significantly lower growth rate of
twelve percent than these two entities. However,
between 2000 and 2010 Escambia County’s growth
trend further diverges from that of Santa Rosa and
Baldwin. Between 2000 and 2010 both Santa Rosa and
Baldwin maintain a similar net population gain while
Escambia’s net population gain lowers by about 28,000
residents, creating an extremely slow growth rate of only
one percent.
Throughout the remainder of this document, the project team will demonstrate how
unattractive characteristics of Escambia discourage people migrating to the region from settling
in Escambia, moving instead to Santa Rosa or Baldwin County.
TABLE 2.1: POPULATION GROWTH AND NET CHANGE IN REGION, 1990-2010
Source: U.S. Decennial Census 1990, 2000, 2010
Growth
Rate
Net
Change
Growth
Rate
Net
Change
Escambia (FL) 12.0% 31,612 1.1% 3,209
Mobile 5.6% 21,200 3.3% 13,149
Baldwin 42.9% 42,135 29.8% 41,850
Escambia (AL) 8.2% 2,922 -0.3% (121)
Okaloosa 18.6% 26,722 6.1% 10,324
Santa Rosa 44.3% 36,135 28.6% 33,629
1990 - 2000 2000 - 2010
County
Unattractive
characteristics of
Escambia discourage
people already migrating
to the region from settling
in Escambia, moving
instead to Santa Rosa or
Baldwin County
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2.1.5 ESCAMBIA COUNTY POPULATION BY CENSUS TRACT
Examining population change by census tract reveals declining population in Pensacola
City and population growth in the census tracts surrounding the City. This suggests outward
migration from the urban core toward the suburbs. Map 2.2 illustrates growth in the north and
southwest census tracts around Pensacola
A pocket of growth is located within the southwest corner of Santa Rosa in region called
Pace. Santa Rosa’s County Economic Development Office informed the Project team that Pace is
a suburban community, which began developing in the early 90s (Stewart, 2014). This region has
been deemed attractive due to its easy commute into Escambia County (via the Escambia River
Bridge) and more laid back, suburban lifestyle (Stewart, 2014).The Santa Rosa Economic
Development Office also informed us that this region has an immense amount of yet to be
developed land (Stewart, 2014).
Three census tracts within Escambia County are
particularly salient: tract 36.06, tract 24, and tract 25. Between
2000 and 2010, census tract 36.03 increased its population from
4,841 residents to 6,653 residents, making it the fastest-growing
tract in the county, with a growth rate of 37.43%. On the
opposite end of the spectrum, tract 24 suffered Escambia’s greatest population decline. With a
negative growth rate of 43.67%, its population decreased from 10,389 residents to 5,852
residents between the years 2000 and 2010.
Interestingly, the borders of tract 24 coincide with those of the Naval Air Station
Pensacola. The project team was informed by a military source at Pensacola Air Station that
there have been no impacts of Defense cuts in the past decade and that the population decline
is due to service members moving off base. Section 4 will discuss this in detail.
Lastly, tract 25 declined in population by 22%. However, this tract consists mostly of
water bodies and its population of 2,136 residents makes it one of the least-populated tracts in
the county. Thus its population decrease is not significant to the forecast.
Northwestern
Escambia suburbs
see a significant
growth between
2000 and 2010
N
ESCAMBIA
COUNTY
SANTA ROSA
COUNTY
BALDWIN
COUNTY
MAP 2.2: ESCAMBIA CHANGE
IN POPULATION
>15% DECLINE
5% DECLINE
+/- 3%
5% GROWTH
>15% GROWTH
PERCENT
POPULATION
CHANGE
2000-2010
Census 2010 (redistricting Data – PL94)
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2.1.6 URBAN AREAS
The 2010 Census classifies an urban area as a densely settled core of census tracts and/or
census blocks that meet minimum population density requirements. They must contain
residential, commercial, and other non-residential urban land uses and have a minimum of 2,500
people, at least 1,500 of which reside outside institutional group quarters. Figure 2.7 shows that,
of all the region’s counties, Escambia has the greatest share of people that live in areas meeting
these criteria.
FIGURE 2.7: PERCENT OF TOTAL POPULATION LIVING INSIDE URBAN AREAS (1990-2010)
Source: U.S. Census
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Baldwin, AL Escambia,AL
Mobile, AL Escambia,FL
Okaloosa, FL Santa Rosa,FL
Perc
ent
Urb
an P
op
ula
tio
n
1990
2000
2010
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2.2 DEMOGRAPHICS
2.2.1 AGE AND GENDER
Figure 2.8 shows a 2010 population pyramid of the county overlaid with that of the state.
While both of them portray a “baby-boom bulge” between the ages of 45 and 64, the state of
Florida has a larger share of older population, which suggests that Escambia County may is not a
retirement destination relative to other parts of Florida.
Escambia County also has a considerably larger share of young people between the ages
of 15 and 30 than the rest of the state. Furthermore, these age cohorts lean a bit more heavily to
the male side. Two factors may help explain this phenomenon: (1) the presence of several
colleges and universities can attract relatively high numbers of young adults that go to the
county to pursue their degrees and then leave. (2) The strong military presence in the county
account for enlisted young men and women, however according to the 2011 Demographics:
Profile of the Military Community, women only account for 14.5% of the military’s active duty
members and 18% of the Selected Reserve (Department of Defense, 2012). Thus, service men
likely account for the relatively larger share of young adult men.
2.2.2 RACE AND ETHNICITY
Racially, most of the county’s population is white (68.9%) but there is a sizable portion of
black population as well (22.9%). Both region and state have a larger share of whites and a
smaller share of blacks than Escambia; though not by a large margin (see Figure 2.9). Other races
are significantly smaller for all three geographical areas and are somewhat similar in proportion,
with the possible exception of (1) the Asian population, whose share is larger than the region but
similar to the state, and (2) other races, whose share is similar to the region but smaller than the
state.
Figure 2.10 shows the ethnic distribution for the county, the region, and the state. Florida
has a much larger proportion of Hispanics than the Escambia and the surrounding area. A strong
Latin-American presence that characterizes the southern and central part of the state drastically
dwindles in the state’s north-west and adjacent Alabaman counties.
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FIGURE 2.8: ESCAMBIA COUNTY POPULATION PYRAMID, 2010
Source: 2010 Census SF1, Table P12
6% 4% 2% 0% 2% 4% 6%
0-45-9
10-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-84
85+
Percent Population
Age
Co
ho
rts
Florida Males Escambia Females Escambia
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FIGURE 2.9: ETHNIC DISTRIBUTION IN ESCAMBIA COUNTY, ITS REGION, AND FLORIDA
68.88%
22.94%
2.75%
0.88%
0.14% 1.26%
3.15%
Escambia County (2010)
White
African American
Asian
American Indian and Alaska Native
Other
two or more races
72.27%
21.02%
1.32%
1.56% 0.10% 1.32% 2.40%
Region (2010) White
African American
Asian
American Indian and Alaska Native
Native Hawaiian and Pacific Islander
Other
two or more races
75.04%
15.96%
2.42%
0.38%
0.07% 3.62% 2.51% Florida (2010)
White
African American
Asian
American Indian and Alaska Native
Native Hawaiian and Pacific Islander
Other
two or more races
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FIGURE 2.10: ETHNIC DISTRIBUTION IN ESCAMBIA COUNTY, ITS REGION, AND FLORIDA
4.72%
95.28%
Escambia County (2010)
Hispanic or Latino
Non Hispanic or Latino
4.08%
95.92%
Region (2010)
Hi…
22.47%
77.53%
Florida (2010)
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2.3 GROUP QUARTERS POPULATION
According to the Census Bureau, “Group Quarters are places where people live or stay, in
a group living arrangement, which is owned or managed by an entity or organization providing
housing and/or services for the residents,” (US Census Bureau, 2011). Group Quarters data can
tell us about the proportion of the population that is institutionalized, in military quarters or in
college dormitories. These are special populations whose population growth (or decline) is not
necessarily condition by the same forces that affect regular population and knowing their data
will help us make better population forecasts (see section 4, Extrapolation).
In 2010, Escambia County had 17,959 people living in Group Quarters, accounting for
approximately 6% of the total population in the county. Besides Escambia, AL, with about 8.4%,
Escambia, FL, has the highest percentage of people living in group quarters.
Table 2.2 shows us the distribution of the Group Quarters population in Escambia, FL.
Noticeably, 70% of the Escambians living in Group Quarters are male. Likewise, the largest
percentage of people living in Group Quarters (36%) are living in military quarters. As expected,
the large presence of the military in Escambia leads to military quarters as the most common
type of Group Quarters. About 82% of those living in military quarters are male.
45 | P a g e
TABLE 2.2: GROUP QUARTERS POPULATION IN ESCAMBIA COUNTY
Total 17,708
Male 12,459 70.4%
Institutionalized population 4,396 24.8%
Correctional facilities for adults 3,925 22.2%
Juvenile facilities 8 0.1%
Nursing facilities/skilled-nursing
facilities458 2.6%
Other institutional facilities 5 0.0%
Noninstitutionalized population 8,063 45.5%
College/university student housing 2,015 11.4%
Military quarters 5,355 30.2%
Other noninstitutional facilities 693 3.9%
Female 5,249 29.6%
Institutionalized population 978 5.5%
Correctional facilities for adults 11 0.1%
Juvenile facilities 4 0.0%
Nursing facilities/skilled-nursing
facilities956 5.4%
Other institutional facilities 7 0.0%
Noninstitutionalized population 4,271 24.1%
College/university student housing 2,775 15.7%
Military quarters 1,134 6.4%
Other noninstitutional facilities 362 2.0%
Group Quarters Population By Sex By Group
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2.4 SOCIOECONOMIC INDICATORS
2.4.1 SOCIOECONOMIC INDICATORS INTRODUCTION
Table 2.3 compares socioeconomic indicators among Escambia, its neighbor counties,
and the state of Florida. The six-county region, comprised of Escambia and surrounding counties,
performs worse than the state in its median household income, per capita income, percent in
poverty, and the share of people 25 and older with a college degree; it also has a lower median
value for owner-occupied housing. Among the region, Escambia performs below average in the
first five columns. This comes to show that Escambia County is at a worrisome condition; indeed,
compared to its neighbors in Florida, it has the worst indicators except for the homeownership
rate. As an example, compare its median household income of $43,806 with its Florida
neighbors’ around $55,000.
TABLE 2.3: SOCIOECONOMIC INDICATORS IN ESCAMBIA, NEIGHBORING COUNTIES, AND FLORIDA
*for Owner-Occupied Housing
Source: 2012 Amerian Community Survey (5-Year Estimates)
2.4.2. EDUCATIONAL ATTAINMENT
Table 2.3 displays the educational attainment for Escambia County, the regional counties,
and the state of Florida. Educational attainment is measured by the percentage of the
population aged 25 and over who has either completed high school or college. Looking at high
school attainment, we see that Escambia County has a higher percentage compared to Florida,
but slightly lower than that of the region. With an 87.1% high school education attainment,
Escambia is competitive in this area. However, when looking at levels of college attainment,
Location
Median HH
Income
Per Capita
Income
Percent
Poverty
Percent
Unemploy
ment
Homeowne
rship Rate 25+ HS
25+
College
Median
Value*
Escambia, FL $43,806 $23,396 17.8% 6.6% 65.4% 87.1% 23.2% $137,300
Santa Rosa, FL $57,491 $27,282 11.1% 6.1% 73.4% 89.3% 25.8% $166,300
Okaloosa, FL $54,118 $28,040 12.5% 5.4% 62.2% 91.2% 27.2% $188,200
Mobile, AL $42,973 $22,581 19.5% 6.7% 67.1% 83.6% 20.3% $105,189
Baldwin, AL $50,706 $26,769 13.3% 5.1% 74.1% 88.4% 27.7% $172,900
Escambia, AL $31,075 $16,294 24.9% 7.3% 72.5% 75.2% 12.2% $85,300
Region $46,695 $24,060 16.5% 6.2% 69.1% 85.8% 22.7% $142,532
Florida $47,309 $26,457 15.6% 6.8% 65.6% 85.8% 26.2% $170,800
47 | P a g e
Escambia’s 23.2% rate is considerably lower than the state average of 26.2% and slightly lower
than the regional average of 24.5%. Furthermore, relative to its Florida neighbors, Escambia
County has the lowest college attainment rate. It is worth mentioning that, with the exception of
Escambia, Alabama, the college attainment rate does not vary widely across the regional
counties. Overall, educational attainment is slightly lower when compared to the Florida
counties but higher compared to the Alabama ones.
2.4.3 UNEMPLOYMENT
In 1990 and 2000, Escambia County experienced unemployment rates at approximately
the same levels of its region and the state, with a decrease of unemployment in all three areas
from one decade to the other. However, when the unemployment rose between 2000 and 2010,
Escambia rose higher than the region (10.3% and 9.3%, respectively). As Table 2.4 shows, this is
intricately related with population growth: the surrounding counties that grew faster than
Escambia between 2000 and 2010 (Baldwin, AL, Mobile, AL, Okaloosa, FL, and Santa Rosa, FL)
also had lower unemployment rates.
FIGURE 2.11: PERCENT UNEMPLOYMENT RATE FOR ESCAMBIA COUNTY, REGION
MEDIAN, AND FLORIDA (1990 – 2000)
0%
2%
4%
6%
8%
10%
12%
1990 2000 2010
Escambia, FL
Region Median
Florida
48 | P a g e
TABLE 2.4: GROWTH RATE AND UNEMPLOYMENT RATE COMPARISON FOR ESCAMBIA, REGION, AND FLORIDA (1990 – 2010)
2.4.3 POVERTY
Poverty rates are “important indicators of well-being” (ACS, 2013). The amount of
residents below poverty in the region varies from 24.9% in Escambia, Alabama, to as low as
11.1% in Santa Rosa, Florida. This is indicated in table 2.3, showing the percentage of the
population below poverty. Escambia, Florida, has 17.8% of its residents living at or below poverty
rate, the highest of the Florida counties. The amount is also larger than the 16.5% six-county
average, and the 15.6% Florida average. This could have important effects on the overall image
and attractiveness that Escambia exudes on potential residents who are looking to move to the
area. The level of poverty in Escambia is especially concerning when juxtaposed to Santa Rosa’s
levels, and could help to explain why Santa Rosa is a more appealing place to live.
2.4.4 CRIME IN ESCAMBIA AND REGION
866 per 100,000 residents of Escambia County were victims of a violent crime in the year
2013. This crime rate is rather extreme, not only for the region but for the state as a whole.
Indeed, Escambia County has the highest violent crime rate in the entire state of Florida. As
shown in Map 2.3, Escambia County has likewise a higher crime rate than its Alabamian
neighbors. Furthermore, Figure 2.12 shows that the overall trend in crime is actually increasing,
making Escambia’s condition extremely worrisome. Escambia’s crime rates sharply contrast with
its neighboring counties of Santa Rosa and Baldwin, which have crime rates of 172 and 215
crimes per 100,000 residents, respectively (Violent Crime Rates, 2013). The combination of a
Growth Unemp. Growth Unemp. Growth Unemp.
Baldwin, AL 25.1% 4.9% 42.9% 3.3% 29.8% 8.7%
Escambia, AL -7.6% 8.1% 8.2% 4.6% -0.3% 10.9%
Mobile, AL 3.7% 6.5% 5.6% 4.4% 3.3% 10.0%
Escambia, FL 12.4% 5.9% 12.0% 4.0% 1.1% 10.3%
Santa Rosa, FL 45.8% 5.6% 44.3% 3.8% 28.6% 9.3%
Okaloosa,FL 30.8% 6.0% 18.6% 3.7% 6.1% 7.9%
Region Median 18.8% 6.0% 15.3% 3.9% 4.7% 9.7%
Florida 32.7% 6.3% 23.5% 3.8% 17.6% 11.3%
1990 2000 2010
49 | P a g e
very high crime rate in Escambia and a very low one in its adjacent counties is likely a major
factor shaping growth in the region.
Santa Rosa’s low crime rates likely stem from the county’s positive socioeconomic
indicators. For example, Santa Rosa has the highest homeownership rate and median income in
the region. Additionally, Santa Rosa has the lowest percentage of poverty within the region. As
will be discussed later, Santa Rosa also has the lowest vacancy rate of all the counties in
Escambia’s region. Such characteristics lessen the need and opportunity for committing crimes.
Likewise, Escambia’s relatively poor socio economic indicators likely contribute to
Escambia’s high crime rates. Pensacola’s high crime rates help to explain why population growth
is declining within this area. Given these conditions, new residents to the region will be more
likely to opt to live in Santa Rosa than in Escambia.
FIGURE 2.12: VIOLENT CRIMES PER 100,000 PEOPLE
SOURCE: Florida Department of Law Enforcement. Crime in Florida, Florida uniform crime report, 1995-
2012 [Computer program]. Tallahassee, FL: FDLE. Florida Statistical Analysis Center.
0
100
200
300
400
500
600
700
800
900
1,000
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Vio
len
t C
rim
es p
er 1
00
,000
Peo
ple
Year
N
ESCAMBIA
COUNTY
SANTA ROSA
COUNTY BALDWIN
COUNTY MOBILE
COUNTY
OKALOOSA
COUNTY
ESCAMBIA
COUNTY
MOBILE
BAY
MAP 2.3: REGIONAL CRIME RATES
172 – 311
312 – 450
451 – 588
589 – 727
728 – 866
VIOLENT
CRIMES
COMMITTED
PER 100,000
PEOPLE
2010 County Health Rankings and Roadmaps, Violent Crime Rates
51 | P a g e
2.5 HOUSING:
2.5.1 INTRODUCTION TO HOUSING
Housing is an important factor to consider when analyzing growth in a county: the
location, magnitude, and value of housing units can inform us where people are choosing to live
and where a high demand for housing exists. Similarly, housing trends can function as proxies for
socioeconomic factors (e.g. ownership characteristics) which may further improve Beards and
Associates’ understanding of population growth in the region.
TABLE 2.5: ESCAMBIA COUNTY HOUSING DATA (2005 – 2012)
Source: U.S Census Bureau, ACS 1 Year Estimates
Table 2.5 shows that Escambia County’s proportion of single-family residential homes has
remained nearly constant since 2005. According the ACS 1 year estimates, the percent of owner
occupied housing units dropped by nearly ten percent between 2011 and 2012. Additionally, the
Table shows that the value of owner occupied homes has declined since 2009, undoubtedly due
to housing crash of 2008. Although home values have yet to increase since the financial crash,
the median rent of homes within Escambia County has risen steadily since 2005.
2.5.2 HOUSING UNITS
The amount of available housing is one housing characteristic that can be used to assess
growth trends. As Table 2.5 shows, the number of Escambia County’s housing units has
Housing Variable 2005 2006 2007 2008 2009 2010 2011 2012
Percent of Housing Units
that are Single-Family70% 70% 68% 68% 65% 64% 67% 67%
Percent of Housing Units
that are Multi-Family22% 22% 23% 26% 27% 28% 27% 27%
Percent of Housing Units
that are: Mobile Home, RV,
or Boat
8% 9% 9% 7% 8% 8% 6% 6%
Percent of Housing Units
that are Owner Occupied69% 67% 69% 69% 64% 67% 67% 59%
Median Value of Owner
Occupied Homes $ 123,500 $ 141,000 $ 148,600 $ 146,500 $ 148,500 $ 139,300 $ 121,400 $ 117,500
Percent of Housing Units
that are Renter Occupied31% 33% 30% 31% 36% 33% 34% 41%
Median Rent of Occupied
Homes $ 667 $ 730 $ 772 $ 785 $ 805 $ 793 $ 858 $ 870
52 | P a g e
remained relatively stable since 1990, having a slightly negative housing unit growth rate
between 1990 and 2000, and a five percent growth rate between 2000 and 2010. Escambia’s
housing unit growth has been slower than every county in the region, save for Escambia
Alabama.
Indeed, according to the Escambia County Property Appraiser’s Office, very little housing
growth is occurring within the county (Smith, 2014). Areas where housing development has
occurred include northern Pensacola, particularly in “Nature’s Trail” and around The University
of West Florida. Nature’s Trail is a single-family housing development in Northwest Pensacola; its
home values range from $250,000-$500,000. Currently the neighborhood consists of 255 homes
but this number is expected to rise to 670 by 2018. One factor that has contributed to the
demand for housing in this area is the relocation of the
Naval Credit Union to north Pensacola. Additionally, multi-
family housing development tends to occur within three
miles of the University of West Florida. This location is in
high demand due to its proximity to the university,
downtown, shopping malls, and naval air base facilities.
Still, overall, Escambia County has seen very little housing
development.
Escambia’s housing unit growth is particularly lower than Santa Rosa, Okaloosa, and
Baldwin, each of which had a housing unit growth rate greater than nine percent. As shown in
Table 2.6, within the Escambia region, Santa Rosa has experienced the most housing
development with growth rates of thirty-three percent in 1990-2000 and twenty-nine percent in
2000-2010. This rapid of housing unit development may a contributor to the county’s
population boom in the 1990s. Additionally, steeply increasing value of homes in the county
indicates that homes are in high demand within Santa Rosa County. Overall, Santa Rosa’s
housing development in the 1990s and 2000s has limited population growth in Escambia County.
As housing units became available in Santa Rosa, Escambia County employees may have began
choosing to live in Santa Rosa County rather than Escambia County. In Santa Rosa, residents are
Escambia’s housing unit
growth is particularly
lower than Santa Rosa,
Okaloosa, and Baldwin,
each of which had a
housing unit growth rate
greater than 9%.
53 | P a g e
in close proximity to Escambia’s employment hub, the city of Pensacola. However, unlike
Escambia County, Santa Rosa residents can enjoy a tranquil living setting with a low crime rate
and a highly rated school district. Due to the abundance of land still available in Santa Rosa
County, it is very likely that this trend will continue into the future. Thus, when considering
growth factors, the trends in Santa Rosa hint that growth in Escambia will likely remain slow.
TABLE 2.6: PERCENT CHANGE OF NUMBER OF HOUSING UNITS IN ESCAMBIA REGION, 1990-2010
Source: U.S. Census Bureau, Decennial Census 1990, 2000, 2010
2.5.3 VACANCY
As shown in Table 2.7, both Florida and Escambia’s region have high vacancy rates.
Escambia’s vacancy rate lies in the middle of the region’s vacancy rates, implying that vacancy is
not a major factor contributing to Escambia’s outlying slow growth within the region. This table
also echoes the theme that Santa Rosa is the top performing county in the region, as it has the
lowest vacancy rate in the region.
For the past several decades, housing development trends have followed population
trends. The counties receiving most of the new housing units have been Santa Rosa and Baldwin.
After Escambia, AL, these counties have been historically the least dense in the region;
conversely, Escambia and Mobile counties, hosting the two major cities in the region (i.e.
Pensacola and Mobile), are significantly denser. While these dense counties have not increased
their number of housing units by a large margin, Santa Rosa and Baldwin have seen a spike in
their number of housing units. Indeed, they have had by far the highest rate of increase of
occupied housing units in the region for the past two decades (see Figure 2.13)
County 1990-2000 2000-2010
Escambia (FL) -1.05% 4.67%
Santa Rosa 33.39% 29.95%
Okaloosa 5.91% 9.22%
Baldwin 8.64% 32.35%
Escambia (AL) -0.41% -0.98%
Mobile -0.69% 5.50%
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TABLE 2.7: VACANCY RATES IN REGION AND STATE, 2008-2012
Source: ACA 5-Year Estimates
FIGURE 2.13: REGIONAL INCREASE IN OCCUPIED HOUSING
Source: U.S. Census Bureau, Decennial Census 2000 and 2010
Vacancy
Rate
Baldwin County, AL 30.0%
Escambia County, AL 16.0%
Mobile County. AL 12.1%
Escambia County, FL 18.3%
Okaloosa County, FL 21.9%
Santa Rosa, FL 12.7%
Region Total 18.4%
Florida 20.4%
-10.00%
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
Dec
enn
ial I
ncr
ease
in O
ccu
pie
d H
osi
ng
2000
2010
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2.5.4 HOUSING VALUES
Housing values are another important housing characteristic that could potentially
impact or shed light on Escambia’s growth. As shown in Figure 2.14, Florida and Escambia Region
Housing Values, 1990-2010, Escambia County’s housing values were lower than Santa Rosa,
Baldwin, Okaloosa, and the state of Florida; and greater than Mobile and Escambia, Alabama
from 1990 to 2010. In the mid-2000s, both Santa Rosa County and Okaloosa County experienced
a steep increase in home values. This may indicate that the demand for housing increased within
these two counties during the 2000s.
FIGURE 2.14: FLORIDA AND ESCAMBIA REGION HOUSING VALUES, 1990-2010
Source: U.S Census Bureau, Decennial Census 1990, 2000, & 2010
55%
60%
65%
70%
75%
80%
1990 2000 2010
Escambia (FL)
Okalossa
Santa Rosa
Baldwin
Escambia (AL)
Mobile
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2.5.5 HOUSEHOLDS
As displayed in Table 2.8, Escambia Region Households: Percentage Family Households,
1990-2010, the percentage of family households throughout the region has remained stable
since 1990. Santa Rosa and Baldwin County have the highest percentages of family households,
with Baldwin County increasing its percentage from fifty-five percent in 1990 to sixty-nine
percent in 2010. Escambia County has the lowest percentage of family occupied housing. This
percentage has stayed almost identical since 1990. This low percentage implies that Escambia
County may not be as family friendly as other counties within the region. This is likely as result of
Escambia County’s high crime rates and poor quality education.
TABLE 2.8: ESCAMBIA REGION HOUSEHOLDS: PERCENTAGE FAMILY HOUSEHOLDS, 1990-2010
Source: U.S Census Bureau, Decennial Census 1990, 2000, & 2010
2.5.6 HOUSEHOLD SIZE
As shown below in Table 2.9, Escambia County has the lowest household size in the
region while Santa Rosa has the highest family size in the region. Overall, the household size
decreased between 2000 and 2010 in all counties except for Mobile and Escambia, Alabama.
2.5.7 SINGLE FAMILY RESIDENCES
Table 2.10 shows the percentage of single-family residences for Escambia and its region.
Single family residences are defined by the U.S Census Bureau as a single unit, detached
dwelling. Often single-family residences are located within the suburbs. As mentioned
previously, census tracts located within the suburbs of Pensacola saw the great increases in the
County 1990 2000 2010
Escambia (FL) 63.1% 66.8% 63.7%
Okalossa 71.0% 70.2% 66.9%
Santa Rosa 63.7% 76.1% 73.0%
Baldwin 55.5% 72.8% 69.9%
Escambia (AL) 66.6% 70.6% 68.6%
Mobile 67.4% 71.1% 68.4%
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percent change of population. Single-family residences could be what are attracting residents to
these suburbs. Interestingly, Escambia County has the lowest percentage of single-family
residence, while Santa Rosa County has the greatest percentage of single-family residences.
Thus, if residents desire to live in single-family residences in suburb communities, Santa Rosa
may present more attractive housing options than does Escambia County.
TABLE 2.9: ESCAMBIA REGION HOUSEHOLD SIZE, 2000-2010
Source: U.S. Census Bureau, Decennial Census 2000 & 2010
TABLE 2.10: PERCENTAGE SINGLE FAMILY RESIDENCES, 2000-2010
Source: U.S. Census Bureau, ACS 1-Year Estimates 2000 & 2010
County 2000 2010
Escambia (FL) 2.45 2.41
Okalossa 2.49 2.43
Santa Rosa 2.63 2.59
Baldwin 2.5 2.46
Escambia (AL) 2.48 2.48
Mobile 2.61 2.56
County 2000 2010
Escambia (FL) 60.8% 65.3%
Okalossa 60.8% 60.6%
Santa Rosa 71.3% 74.0%
Baldwin 60.6% 61.1%
Escambia (AL) 66.3% 70.1%
Mobile 71.0% 72.4%
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2.6 CONCLUSION
Escambia County has seen a dramatic decline in their growth rate, particularly since 2000,
when it experienced a virtual halt in growth. Furthermore, its socioeconomic indicators, such as
educational attainment or poverty rate, are overall worse than Florida and in several cases worse
than the region. This contrasts sharply with its closest neighboring counties of Santa Rosa, FL,
and Baldwin, AL. As prime suburban counties, they are performing much better than Escambia
and have become the new magnets for population growth in the region.
Additionally, it appears that development and population growth in Santa Rosa is
inversely related to that of Escambia County. Santa Rosa’s low crime rates make it a more
attractive community than Escambia.
A N A L Y S I S O F E X I S T I N G
E C O N O M I C B A S E
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SECTION 3.0 ANALYSIS OF EXISTING ECONOMIC BASE
Just as demographic trends in Section 2 were important to understand the present, (and
thus, the future) we must also look at the current economy of Escambia County to see where it is
headed. This section uses three quantitative techniques to analyze which are the most important
industries in Escambia County. We first use a specialization analysis to pinpoint these main
industries and then continue to describe them in detail. Secondly, we then use a concentration
analysis to see determine the share of regional and State jobs captured by Escambia. Finally, we
use a location quotient analysis to examine how Escambia compares to the region, to Florida,
and to the US as a whole as far as their relative size of each industry.
3.1 INTRODUCTION TO ESCAMBIA’S ECONOMY:
Escambia County sits in the heart of the Aerospace Corridor, a concentration of military
and civilian aviation industry that stretches along the Gulf Coast, following I-10 from New
Orleans, Louisiana to Panama City, Florida. The aerospace corridor features the brains and
brawns of people innovating aerospace engineering, manufacturing, electronics, unmanned
aerial systems and much more. The large military presence in the region fuels demand for high
tech firms, who flock to the region to start, join, and develop businesses that serve the defense
industry.
Tourism along the Gulf Coast also drives employment in the region. Beautiful beaches
such as Pensacola Beach attract families on vacation and the wealthy seeking seclusion off on a
barrier island. Images of people relaxing with their feet in the emerald blue and green waters of
the Gulf shores are especially enticing during the cold winter months of the north.
Mobile, Pensacola, and Panama City provide port infrastructure to the region, supporting
substantial trade and spurring some manufacturing. The expansion of the Panama Canal will
likely bring more trade activity to the region as well.
However, recent trends show that the economy of the region in general and of Escambia
in particular, is not performing very vigorously. Table 3.1 shows the disproportionate hit that
61 | P a g e
Escambia and its region suffered between the years of 2006 and 2011: their relative job losses
are nearly three times as much as in the rest of the United States. It is important to view all the
following analysis against this backdrop.
TABLE 3.1: NET JOB GROWTH RATES
*Region includes only Florida counties (i.e. Escambia, Santa Rosa, and Okaloosa, FL)
3.2 ECONOMIC BASE THEORY:
In order to better understand the economic importance of certain industries within
Escambia we will use Economic Base theory to determine relevant industries in the county. For a
more detailed explanation of Economic Base theory and its assumptions refer to Appendix A
Table 3.2 will serve as the source for the discussion below on the Specialization,
Concentration, and Location Quotient analyses. It provides the total number of jobs in Escambia,
the region, the State of Florida, and the United States as a whole.
3.3 SPECIALIZATION ANALYSIS
3.3.1 INTRODUCTION
A Specialization Analysis examines the amount of employment in one industry and
compares it to the total number of jobs the region of study to generate the employment
percentage for that particular industry. Figure 3.1 shows that the sector employing the largest
share of people in Escambia County is the Healthcare industry, comprising nearly one out of
every six jobs in the county.
Total Job
Growth Rate
U.S. -4.41%
Florida -9.57%
Escambia -11.13%
Region* -12.17%
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TABLE 3.2: NUMBER OF JOBS IN NAICS INDUSTRIES IN DIFFERENT REGIONS (2011)
Source: US Census Bureau 2011 County Business Patterns (NAICS) and Florida Department of Economic
Opportunity. Numbers in red are estimates (see Appendix A for details).
The next two largest employers speak to the major role that tourism plays in Escambia
County’s economy: together, the retail and accommodation/food services industries account for
more than 22% of the jobs in this county. These top three sectors, added to Local Government
and Administration, support, waste management and remediation services, account for more
than half of all jobs in Escambia.
Industry
Escambia
Coutny
Employment
Regional
Employment
State
Employment
National
Employment
Agriculture, forestry, fishing and hunting 34 113 11,702 156,520
Mining, quarrying, and oil and gas extraction 56 220 4,751 651,204
Utilities 1,217 1,751 26,966 639,795
Construction 6,197 11,341 288,388 5,190,921
Manufacturing 3,816 6,645 276,352 10,984,361
Wholesale trade 3,410 4,638 279,174 5,626,328
Retail trade 15,241 31,500 940,764 14,698,563
Transportation and warehousing 2,298 4,481 204,981 4,106,359
Information 1,467 3,040 149,771 3,121,317
Finance and insurance 5,138 8,315 331,921 5,886,602
Real estate and rental and leasing 1,496 3,086 143,341 1,917,640
Professional, scientific, and technical services 5,097 12,286 433,745 7,929,910
Management of companies and enterprises 1,217 1,953 134,162 2,921,669
Support/waste mgmt/remediation serv 10,126 14,860 1,172,198 9,389,950
Educational services 3,705 4,431 146,807 3,386,047
Health care and social assistance 18,272 29,976 969,536 18,059,112
Arts, entertainment, and recreation 1,922 2,944 164,264 2,003,129
Accommodation and food services 11,043 24,623 757,932 11,556,285
Other services (except public administration) 4,497 9,868 295,338 5,181,801
Industries not classified 7 19 546 18,452
Federal Government 6,069 14,942 133,992 2,619,051
State Government 3,807 6,232 184,194 4,359,480
Local Government 10,879 21,650 726,610 11,973,790
Total for all sectors: 117,010 218,914 7,777,435 132,378,286
63 | P a g e
Surprisingly, the Federal Government uses only 5.19% of Escambia’s jobs. However, this
reflects only those directly employed by the military. As discussed in section 1.6, the military
(being a significant part of the federal sector) has an extremely large impact in the economy of
Escambia and accounts for more than 66,700 jobs, most of them being in the non-basic sector.
This is more than 57% of all jobs in Escambia (!), making the military one, if not the most,
important employers in the county.
3.3.2 HEALTHCARE:
Table 3.3 shows the top private employers in Escambia County. Each major employer
listed is located within the city of Pensacola, demonstrating that Pensacola is the Employment
hub of Escambia County. The table reveals, not surprisingly, that four of Escambia’s top ten
employers are part of the healthcare sector. These employers include Baptist Healthcare, Sacred
Heart Health systems, West Florida Healthcare and Medical Center clinic.
However, between 2005 and 2013 two of Escambia’s major healthcare employers lost
employees. Sacred Heart Hospital lost 617 employees, while Medical Center Clinic lost 255
employees (Greater Pensacola Chamber, 2013). Corroborating this decline, the NAICS census
data from 2006 and 2011 confirm a net loss of -2.36% jobs in the Healthcare and Social
Assistance sector between these two years--sharply different from the trends in the same sector
for the (1) State of Florida, whose jobs increased by 10.45%, and (2) the U.S., increased by
9.77%.
Given that the Healthcare industry is the largest employer in Escambia, the fact that it
has shrunk in the county while grown elsewhere is worrying news. A stagnant Healthcare sector
is a factor that may hinder a strong population growth in the county
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FIGURE 3.1: SPECIALIZATION ANALYSIS
Source: US Census Bureau 2011 County Business Patterns (NAICS) and Florida Department of Economic Opportunity
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
Perc
ent
of T
ota
l Esc
amb
ia C
ou
nty
Job
s
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TABLE 3.3 MAJOR EMPLOYERS IN ESCAMBIA COUNTY, 2013
Source: Greater Pensacola Chamber
3.3.3 FEDERAL GOVERNMENT
Federal government is another major industry with Escambia County. It is responsible for
roughly eleven percent of Escambia County jobs. This is in large part due to Escambia County’s
military presence. As discussed in section one, Naval Air Station Pensacola plays a large role in
Escambia’s overall economy with an annual economic impact of 6.7 billion dollars. The base
supports 66,000 jobs in Escambia County, which equates to fifty percent of the Escambia County
workforce. This figure includes the 17,000 service members and women who are based at Naval
Air Station Pensacola (Naval Air Station Pensacola). Furthermore, NAS Pensacola’s is part of the
federal government industry and thus it part of Escambia’s basic sector employment. For this
reason, the role NAS Pensacola plays in Escambia’s economy will have a strong influence on job
availability in the non-basic sector.
3.3.4 RETAIL AND ACCOMMODATIONS
As noted by the Visit Pensacola webpage, Escambia’s tourism industry has an economic
impact of $1.2 billion and employs 18,000 residents (National Tourism Week, 2014). The major
destination sought after by Escambia County tourist is Pensacola Beach (Schwalb, 2014). As
tourism’s impact on Escambia’s economy, Retail, accommodations, and food sectors also have a
significant impact on Escambia County. Retail accounts for roughly 13% of Escambia County jobs
while accommodations and food account for nearly 10% of Escambia County’s jobs.
Company Employees Company Description
1 Baptist Health Care 4133 Healthcare
2 Sacred Heart Health Systems 3483 Healthcare
3 Navy Federal Credit Union 3113 Financial Service Center
4 Gulf Power Company 1522 Electric Provider
5 West Florida Healthcare 1300 Healthcare
6 Ascend Performance Materials 830 Manufacturing
7 West Corporation 800 Business, Processing, Outsourcing
8 Medical Center Clinic 500 Healthcare
9 International Paper 475 Manufacturing
10 CHCS Services/iGate 380 Customer Service Center
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Between 2000-2010 Escambia’s tourism industry was hit hard by the economic recession,
hurricane Ivan, and the BP Oil spill. While Escambia County saw a decline in tourism during the
recession, the tourism industry is now beginning to strengthen. Tourism revenues increased by
two percent between 2012 and 2013(National Tourism Week, 2013). In 2013. TripAdvisor's
ranked Pensacola Beach as one of the top 25 Beaches in the U.S (National Tourism Week, 2014).
Thus, it is unlikely that loss within the accommodations and food and retail and trade industries
will continue.
3.3.5 LOCAL GOVERNMENT:
With 9.3% of the workforce, local government accounts for a relatively sizable share of
the Escambia’s jobs. However, Neither the region, nor the state or the country have less than 9%
or more than 10% of their jobs and therefore this sector is not particularly larger when
compared to other geographical areas.
3.4 CONCENTRATION ANALYSIS
Specialization Analysis looks at the number of jobs in each industry compared to the total
number of jobs in that same region of analysis. Concentration Analysis, on the other hand,
compares the number of jobs in the county to the number of jobs in the same industry for a
larger geographical area in order to determine the share of regional employment that the county
captures for a particular industry.
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FIGURE 3.2 REGIONAL CONCENTRATION ANALYSIS
Source: US Census Bureau 2011 County Business Patterns (NAICS) and Florida Department of Economic Opportunity
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
Per
cen
t o
f R
egio
nal
Jo
bs
Co
nce
ntr
ated
in
Esc
amb
ia C
ou
nty
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Figure 3.2 shows that there are certain industries where
Escambia County has relatively high shares of the regional jobs.
If the six-county region had evenly distributed jobs, each county
would have about 17% of regional jobs for each industry.
Therefore, industries accounting for over 30% (utilities, finance
and insurance, management, administrative support and waste
management, and health care) represent a considerable size of all jobs in the given industry. This
implies that Escambia is an employment hub for the industries of utilities, finance, and
management of companies, administration/support, and healthcare. Because Escambia offers
more jobs within these industries, it is likely that residents of neighboring counties seek
employment opportunity within Escambia.
Table 3.3 reveals the percentages of the Escambia County workforce whom live in Santa
Rosa, Baldwin, Okaloosa, Escambia (AL), Escambia (FL), and Mobile. The table demonstrates that
thirty-one percent of the Santa Rosa’s workforce works in Escambia County. This implies that
residents of Santa Rosa County are commuting to Escambia County in order to take advantage of
Escambia’s job opportunities. This further implies that Escambia County is losing resident to
Santa Rosa County because residents who work in Escambia are choosing to live in Santa Rosa
rather than Escambia.
TABLE 3.3: SHARE OF COUNTY WORKFORCE WORKING IN ESCAMBIA COUNTY
Source: ACS 5-Year Estimates Residence County of Workplace Data
County
Percentage of Workforce
that works in Escambia, FL
Baldwin 2.49%
Escambia Al 6.91%
Mobile 0.38%
Escambia FL 89.97%
Okaloosa 1.25%
Santa Rosa 31.26%
Thirty-one percent
of the Santa Rosa’s
workforce works in
Escambia County
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3.5 LOCATION QUOTIENT ANALYSIS
The Location Quotient (LQ) approach is similar to the Specialization and Concentration
approaches in that it compares the total number of jobs in an industry to a reference point. The
LQ analysis combines the specialization and concentration analyses and weighs the percentage
of jobs that each industry represents in Escambia as they compare to the percentage of jobs that
that industry represents for a greater geographical area. By doing this, it helps to identify which
industries are basic and which are not: those that have a higher internal share of jobs than at a
greater geography will be considered basic.
Figure 3.3 shows how Escambia County compares to the region, state, and the United
States as a whole. Whenever an industry has more than a 1.0 in the graph, which means it has a
larger percentage of jobs in that industry than the greater geographical area. The LQ approach
assumes that this means that they are producing more than they actually need locally and are
therefore exporting these services, which in turn bring revenues into the local economy. The
larger the number, the more relevant the industry is to the local economy. The fact that most of
the industry sectors are around 1.0 when compared to the region (green) shows the very similar
industry composition between Escambia and its region. The blue and red bars comparing
Escambia with the U.S. and the State of Florida, on the other hand, show a very different
industry composition. The three most prominent sectors (i.e. those where Escambia has the
highest share of jobs as compared to the region, state, and country) are Utilities, Educational
Services, and Federal Government.
Utilities only capture 1.04% of all Escambia’s jobs and yet, they have an exceedingly large
location quotient ratio when compared to the U.S. and Florida--the reason being that Utilities
account of less than 0.50% in these greater areas. While this implies that a significant portion of
the Utilities industry in Escambia are part of its basic sector, the fact that such an industry is so
small prevents this from being very relevant.
The Location Quotient ratio for Educational Services is above 1.0 for all three
geographical areas. Indeed, as described in section 1.3.7, Escambia is a regional hub for higher
education and its share of universities is larger than average.
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Finally, the largest sector in Escambia relative to the United States and Florida is the Federal Government, which can be
attributed to the large presence of the U.S. military. However, it is worth pointing out that its Location Quotient ratio when compared
to the region is actually smaller than 1.0, demonstrating an even larger share of this sector for Escambia’s neighbors.
FIGURE 3.3: ESCAMBIA COUNTY INDUSTRY LOCATION QUOTIENTS 2011
Source: US Census Bureau 2011 County Business Patterns (NAICS) and Florida Department of Economic Opportunity
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Rat
io o
f Es
cam
bia
In
du
stry
Em
plo
yme
nt
to R
egi
on
an
d U
.S.
Emp
loym
en
t
US
State
Region
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3.6 INDUSTRY TRENDS
The Specialization, Concentration, and Location Quotient analyses area all a frozen
snapshot in the present that inform on the relative size of each of Escambia’s industries and how
they compare to other areas. Yet, in order to understand where the county is going, our project
team decided to analyze the county’s economic trajectory from 2006 until 2011. In order to
control for external factors such as the economic recession of 2008, we studied the region, state,
and country in the same period.
From the three aforementioned analyses, it can be determined that Escambia’s most
important industries are Tourism, the Military, Healthcare, and Education. It is extremely
unfortunate but in Escambia all of these industries are performing worse than the region, the
State, and the U.S. Figure 3.4 shows (1) that the Federal Government (serving as a proxy for the
military), grew by barely over 1% whereas the other areas did so between four and ten times as
much; (2) that Escambia declined the greatest in Retail and Accommodation (proxies for
tourism)--of particular salience is the fact that the county declined by nearly 20% of jobs for
Accommodation whole the state and country had positive gains; and (3) that Escambia and its
region lost jobs in the healthcare sector while the state and country had considerable gains. As
far as Educational Services, the country also performed worse than the other areas, though in
this case this wasn’t by a big margin and its net growth of 10% is fairly strong by itself.
A major contributor to the lackluster job growth rates in tourism, relative to Florida and
the U.S., is the hit that Escambia suffered due to environmental catastrophes: Hurricane Ivan in
2004 and the BP oil spill in 2010 had tangible, detrimental impacts in the tourism industry, the
latter producing an average of -17% downturn in Escambia’s lodging establishments during the
peak season of 2010 as compared to that of 2009 (Visit Pensacola, Inc.).
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FIGURE 3.4: KEY SECTORS NET JOB GROWTH RATES, 2006-2011
7.40%
4.89%
10.65%
1.02%
0%
2%
4%
6%
8%
10%
12%
Federal Government
U.S. Florida
Region* Escambia
9.77% 10.45%
-2.07% -2.36% -4%
-2%
0%
2%
4%
6%
8%
10%
12%
Healthcare and Social Assistance
13.64%
19.35%
10.44% 9.97%
0%
5%
10%
15%
20%
25%
Educational Services
1.54% 2.14%
-13.72%
-18.49%
-20%
-15%
-10%
-5%
0%
5%
Accommodation and Food Services
-6.78%
-10.99%
-13.96% -13.98%
-16%
-14%
-12%
-10%
-8%
-6%
-4%
-2%
0%
Retail Trade
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Not everything is bleak; however, as there are two sectors where Escambia fared
significantly better than others did during this period. While the country and the State of Florida
had flat job growth rates in Management of Companies and Enterprises, Escambia and its region
grew in this sector by more than 70% (see Figure 3.5). Even more remarkable, while the country,
state, and region had negative growth rates for Finance and Insurance, Escambia blossomed
here with nearly 15% of job growth rates. Both of these sectors take a relatively small share of
Escambia’s economy and it is too early yet to determine whether these sectors will have a lasting
impact, but this could be the beginning of a larger trend.
FIGURE 3.5: PROMISING SECTORS NET JOB GROWTH RATES, 2006-2011
-11.44%
-14.55%
-2.88%
14.48%
-20%
-15%
-10%
-5%
0%
5%
10%
15%
20%
Finance and Insurance
0.21%
-2.60%
74.50%
78.40%
-10%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
Management of Companies and Enterprises
U.S.
Florida
Region*
Escambia
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CONCLUSION
Escambia’s key economic sectors are the tourism, healthcare, military, and education
industries. While recent years have been difficult for tourism all across the country, they have hit
particularly harder Escambia and its region. Healthcare, on the other hand, has declined in
Escambia while it has grown in the state and the country. We view the military as a vital yet
stable sector; it is neither growing nor declining and we will assume it will remain as such. The
only of Escambia’s key sectors following a clear growing trajectory is the Education sector; even
though it grew less than the other areas between 2006 and 2011, it had a solid 10% of growth in
that period. Considering the fact that this sector is already fairly large in Escambia, its growth is
extremely promising.
E X T R A P O L A T I O N T E C H N I Q U E
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SECTION 4.0: ANALYSIS OF FUTURE POPULATION
Section 2 and Section 3 of this report have so far analyzed the current Population and
Economic background that are the bedrock for any analysis of the future. Taking into account the
historical patterns of growth and the strength of the economy, we now turn to creating
projections and eventually a final forecast of how the past and the present will shape the future.
This section first evaluates the qualitative factors that are the basis for growth and at the
factors that are hindering growth in Escambia County. This “Forecast Scenario” subsection delves
into local knowledge of the economy and the population that could not be taken into account by
a quantitative model but instead relies on a deep understanding of trends and development in
the region.
We will then show the results from our quantitative techniques and models to produce a
series of different projections for the size of the population in 2040. This section will summarize
the results from these projection techniques and the assumptions the models are based on.
Finally, a “Population Forecast” section will merge the qualitative and the quantitative
methods from the first two subsections into what we believe will be the most likely course in the
future of Escambia County and the number of people who live there.
4.1 THE FORECAST SCENARIO:
4.1.1 FACTORS PROMOTING GROWTH
After being severely battered in the last decade by both the economic recession and the
BP oil spill, we expect the economy of Escambia County to recover slowly in the coming decades.
We expect Escambia’s key industries discussed below to contribute to growth in one way or
another.
Military Sector: As discussed throughout the document, the vital role that the military
plays in Escambia County cannot be overstated. However, while not declining, this sector is not
growing significantly at all in Escambia. Discussing what the future may bring, local employees in
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the Naval Air Station Pensacola informed our team that are not aware of any upcoming changes
that would significantly affect the number of federal dollars Escambia receives for military
spending. We therefore assume that the military sector will grow little or remain stable over the
coming decades and will have a weak but constant contribution to Escambia’s population
growth.
Tourism Industry: The 2008 economic crisis and the 2010 BP oil spill had devastating
effects in the tourism industry of Escambia County. However, we foresee that this major industry
will recover in the next couple of decades, as the national trends in this sector continue to
improve and as the memory of the oil spill fades away.
There are also two trends that will help the tourism industry: (1) the efforts to advertise
the Florida Panhandle as “Florida’s Great Northwest” and the development initiatives in the
region, and (2) the looming rise of baby boomer retirees and “snowbirds.” Although neither of
these trends is inherent to Escambia itself, we expect the county to be positively impacted due
to its location in Florida’s gulf coast.
Healthcare Sector: This key sector presents thorny questions in that it has declined in the
past few years while in the rest of the country it has gone up. However, it is important to notice
that this is a large and established industry in the county and, as such, is less likely to experience
rapid growth. Similar to the military, the healthcare sector is one that serves as a base for the
county’s economy but is not likely to bring much growth. As the county continues to emerge
from the recession, and as baby boomers start to retire en masse, we expect the healthcare
industry in Escambia to grow moderately.
Education Sector: As one of the fastest-growing sectors in Escambia, Education shows to
be a promising industry able to bring investment and people in to the county. We expect
Escambia to continue to be a hub for education and to grow. In particular, our conversations
with various university personnel revealed that the University of West Florida will pursue larger
student populations in their campus in the following decade.
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Growing Industries: Although small at this point, Management of Companies as well as
Finance and Insurance show promising signs of strong growth. If this is continued, they may
become major economic and population drivers. At this point, however, we refrained from
speculating their possible impact given their small share in Escambia’s economy.
4.1.2 FACTORS HINDERING GROWTH
Economic Performance: The overall economic trends in Escambia are not very promising:
for every job loss in the U.S. between 2006 and 2011, Escambia lost three, relative to its
workforce size (see sections 3.1 and 3.6). Not only was the county hit harder during these years
but its core industries of tourism, the military, healthcare, and education grew less than in the
region, the state, and the country. Although we do expect Escambia to recover economically in
the next decades, we do not foresee a strong economic boom but rather a slow, lackluster
growth--save education sector.
Crime: As discussed in section 2.4.4, one of the major factors discouraging people from
choosing to live in Escambia County is the county’s crime rate. Not only does Escambia County
has the highest crime rate in the state of Florida, with 866 violent crimes committed per every
100,000 people in 2012, but also its overall trend is increasing (Violent Crime Rates, 2013). In
stark contrast, Escambia’s neighboring counties, Santa Rosa and Baldwin, had only 172 and 215
violent crimes committed per every 100,000 people in the year 2012. Their lower crime rates
make Baldwin and Santa Rosa much more attractive counties to live in.
School Quality: Another factor discouraging population growth in Escambia County is
school quality (see section 1.5.8). In 2010, with a school district grade of C, Escambia County
ranked in the bottom twenty-five percent of Florida’s school districts. Furthermore, Escambia
County has one of the lowest school grades within the region. The contrast with neighboring
county Santa Rosa could not be starker: the latter has a school district grade of A and ranks as
the second best school district in the state of Florida (Florida School Grades, 2013).
Geography: After a close examination of the local context of Escambia County, our team
has discovered that the factors encouraging growth that we have analyzed might not completely
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benefit Escambia County as a whole. All the industries we have examined and which we predict
will continue to bring in people are located in or near the city of Pensacola and not distributed
evenly throughout the County.
Recent trends in the region have shown that over the past few decades there has been a
shift of people from cities to urban areas surrounding these main cities. This trend holds true for
Escambia County as census tracts within Pensacola have experienced negative population
growth rates and census tracts outside the city borders have experienced positive population
growth (see section 2.1.4). This move to suburban areas is also driven by the fact that most of
the crime-ridden areas in Escambia are within the city of Pensacola.
Unfortunately, Escambia County’s geography is not very well suited to capturing much of
the growth taking place in the outskirts of Pensacola. The major highway in the region, I-10, goes
from east to west which mean that people who choose to live north of Pensacola have longer
commuting times than people who choose to live to the East and West of Pensacola. Since
Escambia is so narrow from East to West, people who want to live close to I-10 and to Pensacola
will end up having to move to neighboring counties, particularly Santa Rosa County to the east.
Map 4.1 demonstrates this phenomenon: while the inner circle that contains the city of
Pensacola experienced negative growth rates, the suburban outer circle increased considerably.
Yet again, the narrow geography of Escambia forces that growth to happen outside its
boundaries. Even if Pensacola experienced high economic growth in the coming years, a
significant share of the attracted population will likely live outside Escambia County.
ESCAMBIA
COUNTY
SANTA ROSA
COUNTY
BALDWIN
COUNTY
MAP 4.1: POPULATION CHANGE IN
PENSACOLA MA
N 0 5 10 Miles
>15% DECLINE
5% DECLINE
+/- 3%
5% GROWTH
>15% GROWTH
PERCENT
POPULATION
CHANGE
2000-2010
Census 2010 (redistricting Data – PL94)
C O N C L U S I O N
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Development in Santa Rosa:
As discussed above, a move away from urban areas and towards surrounding suburbs will
continue to encourage people to relocate to Santa Rosa instead of Escambia. The growth of
Santa Rosa as a bedroom community of Escambia is demonstrated by the fact that nearly a third
of its workforce works in Escambia County. Indeed, with much better school quality and crime
rates, Santa Rosa attracts many of Pensacola’s workers.
To encourage its growth, Santa Rosa has been developing it housing stock, having a
housing growth rate of around thirty percent in both 1990-2000 and 2000-2010. This
development has allowed Santa Rosa to provide Escambia’s workforce with an alternative place
of living and ultimately, divert residents away from Escambia County. As a result, Santa Rosa now
accounts for nearly 35% of the region’s population growth (see section 2.1.2). This trend is likely
to continue given that Santa Rosa has an abundance of promising undeveloped land.
4.1.3 QUALITATIVE INFLUENCE ON FORECAST:
Overall, the qualitative factors indicate that Escambia County will see slow growth in the
upcoming decades. There is only one core industry, education, which shows signs of robust
growth, there rest are either declining or remaining stable. In addition, even if Escambia
experienced rapid job growth in the upcoming years, many of these jobs would be taken by
commuters opting out to live in Santa Rosa.
Escambia’s high crime rate and poor school quality has encouraged this scenario while
Santa Rosa’s housing boom has made living there more feasible. All in all, Escambia is losing its
appeal to potential residents and population growth is expected to remain much slower than the
growth of approximately 30,000 people a decade that had been common in the second half of
the twentieth century.
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4.2 RESULTS FROM THE PROJECTION TECHNIQUES
4.2.1 EXTRAPOLATION TECHNIQUE
One of the most common and simplest ways to make a population projection is with the
extrapolation technique. The technique draws from historical population data to create a
mathematical equation for the population trend to predict future population numbers. In
essence, the technique projects the historical population line into the future using several
formulae for different projections. These projections can be quantitatively evaluated to
determine whether they are sound or not. We subtracted the group quarters population for our
analysis in order to better project the natural growth in the county (see Figure 4.1) and then
added these populations back for the full population projection (see Figure 4.2). A more detailed
explanation of the extrapolation technique and our methodology can be found in Appendix B.
Table 4.1 provides the numbers generated by all extrapolation curves, including the
Linear and Geometric projections, deemed less accurate. The extrapolation technique therefore
tells us that Escambia County’s population in 2040 will be between 300,662 (Gompertz) and
327,629 (Modified Exponential).
TABLE 4.1 COUNTY POPULATION BEST PROJECTIONS, 2010-2030, USING THE EXTRAPOLATION TECHNIQUE
Year Observed Parabol ic Mod Exp Gompertz Logistic
1960 173,829
1970 205,334
1980 233,794
1990 262,798
2000 294,410
2010 297,619
2020 305,750 312,109 310,867 309,518
2030 306,115 320,800 318,183 315,496
2040 300,662 327,629 323,480 319,431
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FIGURE 4.1: ESCAMBIA POPULATION PROJECTIONS EXCLUDING GROUP QUARTERS, 2010-2030
BEST CURVE TYPES BASE PERIOD 1960-2010
0
50,000
100,000
150,000
200,000
250,000
300,000
350,000
400,000
450,000
19
60
19
70
19
80
19
90
20
00
20
10
20
20
20
30
20
40
Pop
ula
tio
n
Year
Observed
Parabolic
Mod Exp
Gompertz
Logistic
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FIGURE 4.2: ESCAMBIA POPULATION PROJECTIONS, 2010-2030
BEST CURVE TYPES BASE PERIOD 1960-2010
0
50,000
100,000
150,000
200,000
250,000
300,000
350,000
400,000
450,000
19
60
19
70
19
80
19
90
20
00
20
10
20
20
20
30
20
40
Pop
ula
tio
n
Year
Observed
Parabolic
Mod Exp
Gompertz
Logistic
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4.2.2 RATIO TECHNIQUES
To make projections about Escambia’s future population, we used three different ratio
techniques. What all three of these techniques have in common is that they compare Escambia
to the West Florida Regional Planning Council (WFRPC) and assume that their relationship will
remain constant in some way. Ratio methods are very valuable and simple to obtain because
they are based on forecasts for larger areas. Forecasts for larger areas are generally more
accurate than forecasts for smaller areas and they are also easier to obtain. These ratio
techniques examine how Escambia compares to the WFRPC and then produce forecasts based
on the future population of the WFRPC.
The constant share method assumes that the population of Escambia will continue to
represent the same proportion of the WFRPC. The shift share method calculates the difference
between the proportion Escambia was in one particular year and how much it changed by
another year and assumes that each subsequent decade will continue to see the same change.
The share of growth method examines growth in the region and how much of it was captured by
Escambia and then assumes Escambia will continue to capture the same share of growth in the
future (Klosterman, 1990).
In Figure 4.3, we present the results of two of the three Ratio Methods. We can see that
the constant share method shows high population growth, projecting a population of about
380,000 in 2040. The Shift Share method, on the other hand, produces a large decrease in
population and projects about 270,000 people in Escambia County in the year 2040. We believe,
based on qualitative evidence, that the Share of Growth method represents a more accurate
depiction of the possible future and projects a population in 2040 of approximately 316,000
people. For a more detailed analysis of ration techniques, refer to Appendix B.
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FIGURE 4.3 BEST PROJECTIONS USING THE RATIO TECHNIQUE
4.3 FINAL POPULATION FORECAST
Escambia’s population growth pattern was broken in the decade from 2000 to 2010,
when its growth accounted to barely over 3,000 while before it had been around 30,000. This
can be explained by the county’s weak economic performance, its increasingly high crime rates,
and its relatively poor school quality. In addition to that, its thin shape prevents the county from
capturing much of the suburban growth taking place in the past decades. Given these
limitations, it is highly unlikely that Escambia will regain its previous growth rates.
If crime continues to increase, there are no improvements in the county’s schools, and
there are no industries that endure a sustainable growth, Escambia’s population by 2040 could
be as low as 307,028 (see Figure 4.4). On the other hand, if the county drastically improves its
crime and school issues, if its educational sector continues to grow, and if its core industries
become robust once again, Escambia’s population could be as high as 345,414.
0
50,000
100,000
150,000
200,000
250,000
300,000
350,000
400,000
2000 2010 2020 2030 2040
Pop
ula
tio
n
Year
Observed
Constant
Growth
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FIGURE 4.4 ESCAMBIA COUNTY POPULATION FORECAST, 2010 – 2040
350,914
301,528
320,793
0
50,000
100,000
150,000
200,000
250,000
300,000
350,000
400,000
450,000
19
60
19
70
19
80
19
90
20
00
20
10
20
20
20
30
20
40
Pop
ula
tio
n
Year
Observed
High
Low
Forecast
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Our project team believes its population will be closer to the bottom than to the upper
end: two of Escambia’s core sectors, namely healthcare and tourism, have been in decline and
are faring worse than the region, the state, and the country; and school quality and crime rates
don’t show signs of getting any better--the latter having in fact an adverse tendency. However, it
is important to acknowledge the fact that Escambia was not only affected by the 2008 recession-
-something which affected the entire country--but was also hit considerably by hurricane Ivan in
2004 and the BP oil spill in 2010--events that affected only the region. Our team believes the
county will recover to a certain degree from these disasters as well as from the 2008 economic
recession and will grow with a faster rate than that in the 2000’s.
As shown in Table 4.2, we foresee growth from 2010 to 2020 to be almost twice as high
as the nearly flat rate between 2000 and 2010, reflecting our expectation of Escambia’s
economic recovery. In particular, we believe the tourism industry will not only gain ground after
the recent disasters but also improve as the effects of the 2008 recession continue to attenuate.
Additionally, not only will Escambia’s military will continue play a small contribution to
the county’s growth for the coming decades but its education industry shows signs of expanding.
We therefore forecast the county’s growth rate to slowly increase over the years from 2020 and
onwards.
TABLE 4.2: ESCAMBIA COUNTY POPULATION FORECAST 2020-2040
Year Population Net increase
Percent
Change
1960 173,829
1970 205,334 31,505 18.12%
1980 233,794 28,460 13.86%
1990 262,798 29,004 12.41%
2000 294,410 31,612 12.03%
2010 297,619 3,209 1.09%
2020 304,689 7,070 2.38%
2030 312,568 7,879 2.59%
2040 320,793 8,224 2.63%
Ob
serv
edFo
reca
st
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5.0 CONCLUSION
Growth in Escambia County was consistent between 1960 and 2000 as roughly 30,000
people were added per decade. However, it halted between 2000 and 2010 as the county added
only a little over 3,000 people. Our project team found that Escambia County’s growth began
slowing as early as 2002, six years before the 2008 recession, suggesting that factors other than
the recession caused Escambia County’s growth to slow. Furthermore, Escambia’s 2000-2010
population growth rates dropped much more dramatically than did the state’s and the region’s.
Even after controlling for localized impacts such as hurricane Ivan in 2004 and the BP oil spill in
2010, Escambia’s growth stalled while the surrounding region kept growing persistently.
We identified four core industries that have historically pushed the county’s economic
and population growth: tourism, the military, healthcare, and education. From these, only
education shows a clear trend towards generating growth in the county, while the tourism and
healthcare show a net decline in jobs. This is not a couple of isolated cases: most industry sectors
have declined in Escambia between 2006 and 2011, and the county’s net job loss during this
time was greater than the state, which in turn was greater than the country. As the county
rebounds from the 2008 recession and the 2010 oil spill, however, we expect to see tourism and
healthcare to grow once again. However, it is uncertain the degree to which Escambia will grow
economically. The military has been a historically crucial sector in Escambia and currently has a
45% impact on the county’s GRP. From among its four core industries, the military has remained
the most stable and we do not foresee any major change in its presence in the region.
Besides its unimpressive economic performance, the county also experiences
considerable challenges to its growth, namely its high crime rates and relatively poor school
quality. Not only does the county have the highest crime rate in the whole state of Florida, but
also this rate is rising (Violent Crime Rates, 2013). Escambia’s 866 violent crimes committed per
every 100,000 people in 2012 contrasts strongly with its adjacent neighbors Santa Rosa and
Baldwin, with a rate of 172 and 215 violent crimes per every 100,000 people in the same year.
When it comes to public education Escambia is equally disadvantaged, especially as it compares
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with its Florida neighbors: in 2010, with a school district grade of C, Escambia County ranked in
the bottom twenty-five percent of Florida’s school districts. Its neighbor Santa Rosa County, on
the other hand, has a school district grade of A and ranks as the second best school district in
Florida (Florida School Grades, 2013).
These challenges reveal that even if Escambia County gains a considerable amount of
jobs in the near future, these would not necessarily lead to a considerable growth within
Escambia’s borders. The fact that already thirty percent of Santa Rosa's workforce work in
Escambia corroborates this phenomenon. In essence, residents of Santa Rosa County get the
“best of both worlds” enjoying their county’s better school quality and lower crime rates while
utilizing Escambia County’s job opportunities. This trend is likely to continue due to Santa Rosa’s
abundance of available land for development.
Beards and Associates has determined that Escambia will grow faster than it did in the
past decade, but much more modestly than in the decades leading to the turn of the century:
from 2010 to 2040, we predict an average growth rate of 2.5%, moving from 297,619 in 2010 to
320,793 in 2040. The slow growth rate is grounded on the observation that there are no clear
signs that Escambia’s socioeconomic indicators are improving. This rate, however, is higher than
in the past decade as we believe the county’s tourism will rebound and its education sector will
generate some growth of its own.
Escambia might go through some economic changes as it settles in the twenty-first
century. Big established sectors like the healthcare industry might see some decline, while there
is the potential for smaller ones, like finance and insurance, to rise. These trends, however, are in
too early of a stage to be the basis for a forecast and, as it stands, Escambia will experience a
modest but constant growth, fueled by the ever-present military, a rebounding tourism, and,
perhaps most importantly, its education industry.
A P P E N D I X A
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APPENDIX A: METHODOLOGICAL DETAILS ON POPULATION AND ECONOMIC ANALYSES
A.1 DATA SOURCES
The project team was required to obtain both public and private employment data in
order to calculate Escambia’s location quotients and specialization and concentration analysis.
Private data was collected through the U.S Census Bureau’s economic census. Public data was
collected from the United States Public Sector Employment Data 2011 and the Florida
Department of Economic Opportunity. However, not all private industries disclose their exact
number of employees. Rather, this data is hidden under letters, which represent a range of
values. For such ranges, the project team was required to estimate what the exact number of
employees was. This was done by taking the midpoint of each unknown range of values and
adjusting them up or down, relative to their size, until sum of all jobs reached the reported total.
A.2 SPECIALIZATION ANALYSIS
The specialization approach is used to examine how important an industry is to the local
economy. This is obtained by dividing the number of jobs from the industry in question to the
total number of jobs in the economy, which is represented by the equation below:
Ni= (Local Employment in industry I /Total Local Employment)*100
This technique therefore gives us the share of county jobs that each industry sector has.
NAICS 2 digit level data and the data from the Florida department of Economic Opportunity was
used to make the above calculations.
A.3 CONCENTRATION ANALYSIS
A different but related technique is the Concentration Analysis. As represented in the
equation below, concentration analysis looks at the number of jobs in an industry in a particular
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region and compares it to the number of jobs in the same industry, in a larger region. “This
illustrates how important a given local sector is to the regional economic sector” (Chapin, 2014).
Ni= (Local Employment in Industry i / Regional Employment in industry i) *100
When calculating values for the concentration analysis, Beards and Associates compared
Escambia’s economy to the regional and state economy. As mentioned in section 3, we were
forced to using only the Florida counties (Escambia, Santa Rosa, and Okaloosa) to define the
region given that public-sector job data was not available for the Alabama counties.
A.4 LOCATION QUOTIENT (LQ)
Economic Base theory makes certain assumptions that are important to acknowledge.
First, it assumes that industries in a community can be divided into basic and non-basic sectors.
The basic sector comprises industries that are dependent not on the local economy but on other
factors outside of it. A simple example could be a small gold-mining town that exports most of its
gold and receives important revenue from it. In this hypothetical example, the small town has a
basic sector of gold mining that brings in resources to the local economy.
In contrast, the non-basic sector represents industries relevant to the local economy. In
our theoretical example of the gold-mining town, the non-basic sector would comprise those
industries that serve the local residents of the community, like restaurants and retail stores.
These, however, are supported by the basic sector. After all, in our small town the main
customers of such restaurants and stores would precisely be the gold miners and executives. The
basic sector is therefore to the local economy since it brings outside dollars into the community,
spurring economic growth.
The location quotient approach examines how much an industry is specialized in
Escambia compared to another area of interest. In other words, an LQ approach looks at the
ratio of an industry’s share of the local economy and compares it to the share of the national or
state economy (Klosterman, 1990).
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The equation used to calculate the location quotient of a particular industry is shown
below:
LQi = eit/eT
t/Eit/ET
t
where:
• eit=Local employment in sector i at time t
• eTt = Total local employment at time t
• Eit= National employment in sector i at time t
• ETt = Total national employment at time t
When industries have more than a 1.0 in a certain industry it means that the industry can
be considered basic and they are producing a larger share than they are expected to. These
industries are thus seen as very important to the economy as it is likely that these are products
or services that are sold to other regions, bringing new revenue into the county (Klosterman,
1990).
A P P E N D I X B
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APPENDIX B: POPULATION PROJECTIONS TECHNICAL APPENDIX
B-1 EXTRAPOLATION TECHNIQUE
B.1.1 EXTRAPOLATION TECHNIQUE INTRODUCTION:
The population forecast we presented for Escambia County used the Extrapolation
Technique to analyze and predict the future population for the County. The extrapolation
technique looks at historical population trends and graphs a line between them. The line is then
extended into the future to make population projections. Many different lines can be used to
make different projection and then the analyst must decide which of these lines produces the
most accurate projection.
The simplest curve used to graph historical population data is the linear curve. This is a
simple straight line that has a constant slope and therefore assumes that growth remains
constant over time. The geometric or exponential curve is a line, which assumes that a constant
growth rate is compounded to create rapid increases in population. This is the curve that is
visible in a savings account which yields interest. As there is more money, the growth rate will
continue to increase over time. The parabolic curve, also called the second-degree curve, creates
a concave or convex curve that increases very rapidly because the growth rate changes
constantly. There are other types of curves that take into account the existence of a limit to
growth and therefore do not continue growing forever, as the three previous lines had. These
are called asymptotic curves because they assume that population will grow or reach until it
approaches an asymptote or limit. The modified exponential curve, the Gompertz curve and the
logistic curve all assume that the growth rate increases first but then slows down, as it gets closer
to the asymptote. These curves are normally seen in nature as organisms growth is fast at first
but then hindered by physical limits or resources (Klosterman, 1990).
Our analysis examined how each of these curves would fit the historical population data
that we had and in the end we used our qualitative data about Escambia County to see which
curve most accurately depicts the population. Populations pass through different stages and it is
possible that a curve that was once very accurate in describing the population might be useless
and a new line could become more appropriate. We plotted all six of the curves and in the end
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decided that the most appropriate ones were the Parabolic, Modified Exponential, Gompertz
and Logistic curves.
However, a special caution should be made about special populations: their growth and
decline are not determined by the same factors as those affecting the rest of the population and
for that reason they must be treated differently.
TABLE B.1: GROUP QUARTER POPULATION IN ESCAMBIA, FL
*Estimates
Source: U.S Census Bureau
Since the data for group quarter populations is considerably more accessible than the
rest of the special population, we will use it to separate it from the rest of the population and
perform and extrapolation analysis to the non-group quarter population. Table B.1 shows the
group quarter population in Escambia County from 1960 to 2010. Because the census of 1960
did not include that information, Beards and Associates decided to assign the same number as
the decade after, 1970. Figure B.1 shows the size of each group quarter category for the year of
2000 and 2010: while correctional institutions, nursing homes, and other institutions declined,
student housing, military quarters, and other non-institutional facilities increased. Upon further
investigation, only student housing seems to have a clear trajectory towards increasing in
numbers; the rest are a bit more uncertain (University of West Florida Campus Master Plan,
2012).
Year
Group Quarter
Population
Share of total
population
1960 8,741* 5.0%*
1970 8,741 4.3%
1980 7,622 3.3%
1990 9,560 3.6%
2000 21,966 7.5%
2010 17,959 6.0%
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Therefore, we decided to hold constant the group quarters population of 2010 constant,
assuming that while some sectors might increase and other decrease, the overall group quarter
population will remain roughly constant through 2040. Figure B.2 shows all the extrapolation
projections for the non-group quarters population while figure B.3 shows them with the added
group quarters.
FIGURE B.1: GROUP QUARTERS COMPOSITION, 2000-2010
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
Pop
ula
tio
n
2000
2010
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FIGURE B.2: NON-GROUP QUARTER PROJECTIONS, 2010-2030
ALL CURVE TYPES BASE PERIOD 1960-2010
FIGURE B.3: COUNTY PROJECTIONS, 2010-2030
ALL CURVE TYPES BASE PERIOD 1960-2010
0
50,000
100,000
150,000
200,000
250,000
300,000
350,000
400,000
19
60
19
70
19
80
19
90
20
00
20
10
20
20
20
30
20
40
Pop
ula
tio
n
Year
Observed
Linear
Parabolic
Mod Exp
0
50,000
100,000
150,000
200,000
250,000
300,000
350,000
400,000
19
60
19
70
19
80
19
90
20
00
20
10
20
20
20
30
20
40
Pop
ula
tio
n
Year
Observed
Linear
Parabolic
Mod Exp
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B.1.2 INPUT EVALUATION PROCEDURES
Once the extrapolation curves were produced the project team had to identify the
projection which offered the reasonable projections for Escambia’s future. This was achieved by
using two different procedures, input evaluation and output evaluation. Each of the curves
mentioned above have different growth assumptions and the input evaluation procedure
identifies the curve whose growth assumptions best resemble the observed data. The curve
which most closely corresponds with the observed data is deemed the most appropriate curve
(Klosterman, 1990).
Coefficient Relative Variation (CRV):
The CRV functions as an input evaluation test; it is an evaluation statistic that is used to
assess which curves growth assumptions most correlate with the observed data (Klosterman,
1990). Hence, this statistic requires an understanding of each curve’s growth assumptions. The
CRV’s evaluation formula is “the standard deviation expressed as a percentage of the absolute
value of the mean” (Klosterman, 1990, p.40).
CRV+ s/z * 100
This statistic allows each curve to be expressed in common terms and thus compared.
The curve with the lowest CRV value is the most appropriate curve.
B.1.3 OUTPUT EVALUATION PROCEDURES:
The second type of procedure used to evaluate extrapolation curves is output
evaluation. This procedure assess how accurately projections match observed data (Klosterman,
1990). “The procedures assume that the extrapolation curve that best fits past growth trends
will most accurately predict future trends” (Klosterman, 1990, p.42).
Mean Error (ME)
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The ME is an output test that computes and sums the deviations between each set of observed
and estimated values (Klosterman, 1990).
ME: Sum(Y-Yc)/N
Y=observed value for dependent variable
Yc=estimated value for dependent variable
N=number of observations
ME’s values closer to absolute zero are better because values closer to absolute zero
indicate that projections are closer to observed data. While this test is less insightful than CRV
and MAPE, in that negative and positive values cancel each other out, it is still useful in that it
indicates if a curve is consistently high or low in fitting to the observed data. This provides an
indication of the bias of the curve.
Mean Absolute Percentage (MAPE)
The MAPE is another output test that is “expressed as a percentage that offers a direct
comparison of the level of error across the various curves” (Chapin, 2014).
Sum ((|Observed - Estimated|)/Observed) / N *100
Y=observed value for dependent variable
Yc=estimated value for dependent variable
N=number of observations
Lower MAPE values indicate that the projections are closer to observed data; thus lower
MAPE values are better than high MAPE values. Unlike the ME, the MAPE evaluates the total
estimation error. Furthermore, the MAPE is considered to be the most useful evaluation
technique because it is “unaffected by the number of observations, making it appropriate for
comparing estimates for different data sets and different number of observations (Klosterman,
1990, p.44).
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B.1.4 CRV, ME, AND MAPE FINDINGS
TABLE B.2: EVALUATION OF EXTRAPOLATION CURVES
Having subtracted the group quarter population from the rest of Escambia’s population,
we applied six different extrapolation curves to the observed data; these are listed in Table B.2
(highlighted in yellow are values that should raise a bit of caution and in red those that should be
used with a great deal of caution). As the Table MAPE analysis shows, the Linear and Geometric
curves performed significantly worse in fitting the observed data and for this reason were not
included. Even though the Parabolic curve had a considerably higher CRV score than its
counterparts, it was, after the Logistic curve, the best to perform in the MAPE analysis and for
that reason we opted to include it as an overall accurate curve. Figure B.4 shows the best-fitting
curves for the observed data and their respective population projections.
Adding the group quarter population makes the population slope between 2000 and
2010 even flatter, as that population was larger in 2000 than in 2010. Figure B.5 shows these
same extrapolation curves but with the added group quarter population, including in the years of
2020-2040, where a constant group quarter population of 17,959 is assumed to remain
constant.
CRV ME MAPE
Linear 43.4 0 2.84%
Geometric 54.9 94 4.07%
Parabolic 78.4 0 0.88%
Mod Exp 35.5 0 1.21%
Gompertz 32.3 -42.8 0.97%
Logistic 29.1 -44.8 0.75%
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FIGURE B.4: NON-GROUP QUARTER PROJECTIONS, 2010-2030
BEST CURVE TYPES BASE PERIOD 1960-2010
FIGURE B.5: ESCAMBIA COUNTY PROJECTIONS, 2010-2030
BEST CURVE TYPES BASE PERIOD 1960-2010
0
50,000
100,000
150,000
200,000
250,000
300,000
350,000
400,000
450,000
19
60
19
70
19
80
19
90
20
00
20
10
20
20
20
30
20
40
Pop
ula
tio
n
Year
ObservedParabolicMod ExpGompertzLogistic
0
50,000
100,000
150,000
200,000
250,000
300,000
350,000
400,000
450,000
19
60
19
70
19
80
19
90
20
00
20
10
20
20
20
30
20
40
Pop
ula
tio
n
Year
Observed
Parabolic
ModExp
Gompertz
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B-2 RATIO TECHNIQUE
B.2.1 RATIO TECHNIQUE INTRODUCTION
The Ratio Technique is a methodology to project future populations for Escambia County
based on its share of population and growth in contrast to a pattern area. All three-ratio
methods we used assume a constant relationship in some aspect of the growth of Escambia
County and the West Florida Regional Planning Council (WFRPC). The WFRPC is a regional entity
combined of Bay, Escambia, Holmes, Okaloosa, Santa Rosa, Walton and Washington
Counties. We then used the population projections created by the Bureau of Economic and
Business Research (BEBR) for the WFRPC and we produced projections for Escambia County.
TABLE B.3 BEBR PROJECTIONS FOR THE WFRPC
Forecast 2015 2020 2025 2030 2035 2040
Low 876,100 886,700 892,800 894,000 890,600 883,400
Medium 930,700 978,200 1,023,800 1,066,500 1,106,300 1,144,300
High 989,900 1,070,800 1,153,100 1,236,200 1,320,000 1,405,200 Source: BEBR
B.2.2 CONSTANT-SHARE RATIO METHOD
The constant share method looks at how our target area compares to a larger area and
assumes that the proportion our target area represents will remain constant over time. To make
projections using the constant share method, we first divide the population of Escambia County
in 2010 by the population of the West Florida Regional Planning Council (WFRPC) in 2010 to find
that the population of Escambia County represents 33.12% of the WFRPC.
We then assume that Escambia will keep representing 33.12% of the population of the
WFRPC and we use BEBR projections for the WFRPC’s future population. We multiply 33.12% by
the future populations of the WFRPC as projected by BEBR, which are shown in table B.3, and we
are able to make projections for Escambia County, which are displayed in table B.4.
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Table B-4 Escambia County Constant Share Method Projections 2015-2040
Forecast 2015 2020 2025 2030 2035 2040
Low 290,189 293,700 295,721 296,118 294,992 292,607
Medium 308,274 324,008 339,112 353,255 366,438 379,025
High 327,883 354,679 381,939 409,465 437,222 465,442 Source: BEBR and US Census Bureau
B.2.3 SHIFT-SHARE RATIO METHOD
The shift-share examines how Escambia County changed as a proportion of the WFRPC.
We look at what proportion of the WFRPC was comprised of Escambia in 2000 and in 2010. We
found that in the year, 2000 Escambia County comprised 36.3% of the WFRPC and in 2010 it
comprised 33.1% of the WFRPC. This means that Escambia County shrank as a proportion of the
WFRPC by 3.2% in a decade. The shift-share method assumes that Escambia’s proportion of the
WFRPC will be reduced by 3.2% each decade.
Using this method, we can estimate that in 2020 Escambia County will comprise 29.9% of
the WFRPC, 26.8% in 2030 and 23.6% in 2040. We then multiply these numbers by the BEBR
projections for the WFRPC (which are in table B.3) and we obtain population projections for
Escambia County, as shown in Table B.5.
TABLE B.5 ESCAMBIA COUNTY SHIFT-SHARE PROJECTIONS
Forecast 2020 2030 2040
Low 265,512 239,278 208,358
Medium 292,911 285,447 269,893
High 320,639 330,867 331,429 Source: BEBR and US Census Bureau
B.2. 4 SHARE OF GROWTH METHOD:
The share of growth method looks at growth in both Escambia County and WFRPC and
sees what percentage of the growth in the larger area was comprised of growth in the smaller
area. We see that between 2000 and 2010 the WFRPC grew by 87,525 people. In that same time
interval, Escambia County grew by 3,209 people. This means that of all the growth in the WFRPC,
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3.7% of it accounted for the growth in Escambia County. This method then assumes that for each
decade of growth in WFRPC, 3.7% of that growth will be from Escambia County.
We then look at how much the WFRPC is expected to grow each decade and multiply
that growth by 3.7% to obtain the resulting population projections for Escambia County.
FIGURE B-5: PROJECTION RESULTS FROM THREE RATIO TECHNIQUES
Source: BEBR and US Census Bureau
TABLE B-6 ESCAMBIA COUNTY POPULATION AND PROJECTIONS (IN BLUE) USING RATIO METHODS
Constant Share
Shift Share
Share of Growth
1990 262798 262798 262798
2000 294410 294410 294410
2010 297619 297619 297619
2020 324,008 292,911 303,833
2030 353,255 285,447 310,720
2040 379,025 269,893 316,789 Source: BEBR and US Census Bureau
0
50000
100000
150000
200000
250000
300000
350000
1990 2000 2010 2020 2030 2040
Pop
ula
tio
n
Low
Medium
High
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After looking at the results from the three ratio techniques we decided that the share of
growth method is the most appropriate and the one more in accordance to what we expect from
the qualitative data we collected.
The constant share method does not look at changes over time and does not take into
account whether the share is growing or shrinking and for this reason, we get the largest
population projections from this method.
The shift share ratio is also unlikely to predict accurate population growth for Escambia
County. There is no reason to believe that Escambia’s share of the WFPRC’s population will
continue to decrease by exactly 3.17% each decade. The population of Escambia might have
decreased more than the region during the recession starting in 2008 because it had the most to
lose. As people were affected by loss of income, tourism and finance, two of the main drivers of
the Escambia economy were severely affected. For these same reasons, we expect that a
rebounding economy will also benefit Escambia County largely that the nearby counties given
that it is a regional hub in these industries.
The share of growth method produced the results we think most accurately reflect future
population growth. We found that if we saw the share of the growth that Escambia captured
between 2000 and 2010 we found a proportion of 3.7%. Given that the 2000s was an anomalous
decade because of the recession we decided to average the 2000s with the 1990s to obtain a
more accurate estimate of the share of growth that Escambia County captures.
B.2.5 GROUP QUARTER CONSIDERATION
We also decided to see how removing the group quarters population and creating a
forecast of the normal population changed our results. We subtracted the group quarters for our
base years, made the projections and then added the group quarters population back. As we
have touched on before, we believe the group quarters population will remain fairly stable at
aroudn 18,000 people. The results from this projection only reduced the forecasts by about
3,000 people, as we can see in Figure B.6.
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FIGURE: B.6: RATIO TECHNIQUES HOLDING GROUP QUARTER POPULATION CONSTANT
Source: BEBR and US Census Bureau
FIGURE B.7: RATIO TECHNIQUE WITH FLORIDA
Source: BEBR and US Census Bureau
0
50000
100000
150000
200000
250000
300000
350000
400000
1990 2000 2010 2020 2030 2040
Constant Share
Shift Share
Share of Growth
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B.2.6 COMPARISON TO FLORIDA
We also compared Escambia to the State of Florida using these three ratio techniques
but, as Figure B.7 shows, the numbers are either extremely high or extrely low to be compatible
with our qualitative data. For this reason, we believe comparing Escambia to Florida is not a
good assumption and we did not include the results on the report.
B-3 POPULATION FORECAST
Upon studying the best-fitting curves for Escambia’s population projections, our project
team noticed the range between the highest and lowest 2040 projection was less than 30,000.
Given the uncertainty over Escambia’s economic future as well as our desire to consider a high-
growth and low-growth scenario, we decided to expand this range by adding a “High” and “Low”
projection curves (see Table B-7). The “High” curve was obtained by averaging the Constant
Share and the Share of Growth ratio techniques while the “Low” projection was obtained by
averaging the Parabolic and Logistic extrapolation curves.
TABLE B-7: BEST-FITTING POPULATION PROJECTION CURVES FOR ESCAMBIA
Informed by our research in qualitative factors, our project team sought a forecast that
presented a slow, somewhat steady growth considerably lower than its past growth in between
1960 and 2000 but faster than the decade of 2000-2010. We got close to reaching this by
averaging all the best curves shown in Table B-7 save the low-range parabolic curve. However,
these numbers reflected an exceedingly high growth rate in 2010-2020, somewhat out of touch
with the past trend; they also had an increasingly shrinking growth rate towards 2040. We
Year Observed LinearShare of GrowthParabolic Mod Exp Gompertz Logistic High Low
1960 173,829
1970 205,334
1980 233,794
1990 262,798
2000 294,410
2010 297,619
2020 332,906 302,732 305,750 312,109 310,867 309,518 313,112 307,634
2030 356,548 308,400 306,115 320,800 318,183 315,496 330,284 310,806
2040 380,191 313,393 300,662 327,629 323,480 319,431 345,414 307,028
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believe, on the other hand, that population growth will increase slowly over the years and
therefore decided to slightly adjust these values by reducing the values for 2020 and 2030 by
1.5% and those of 2040 by 0.6%, as seen in Table B-8.
TABLE B-8: FINE ADJUSTMENTS TO PROJECTION VALUES FOR FINAL FORECASTING
Year Original Adjusted
2020 309,329 304,689
2030 317,328 312,568
2040 322,729 320,793
R E F E R E N C E S
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SECTION 3.0
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SECTION 4.0
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APPENDIX A
Klosterman, R. (1990). Community Analysis and Planning Techniques. New York: Rowman and
Littlefield Publishers Inc.
APPENDIX B
Chapin, T. (2014, March). Evaluating Extrapolation Curves is Akin to Judging a Dog Shows.
Tallahassee, Fl, United States.
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