Population Dynamics
Assignment 1
The purpose of this assignment was to introduce us to ways of looking at population through the census. Using terms like population pyramid, dependency ratio, and location quotient, these calculations and help drastically when looking at starting a new business. All these terms along with being able to read and comprehend the United States census would allow for a business geographer to make a calculated decision on where a business could thrive along with the view of people that the business would be geared towards.
The first part of this assignment dealt with the creation of a population pyramid. To be able to do this I had to download information from the census website. I was asked by a business investor to steer him in the right direction allowing him to understand the population structure of Colorado Springs as well as the overall service sectors of the city.
I first began by downloading the age and sex data for Colorado Springs from the census website. This gave me the breakdown of different age groups and the sex. My data was based of off the ACS 5- year estimates for the city. Once I found the data on the census website I then downloaded it and brought it into excel for further processing. The next step was to calculate the percentage for both male and female for Colorado Springs. This was an easy process as I was able to compute the equation right in excel. My final table once it was neat and all the equations were computed looked like this.
The next step was to actually create the population pyramid. Again I was able to create this right in excel as I was able to highlight the data that I wanted to be on the pyramid. I chose the age column along with the %Male and %Female columns. When I had these three columns highlighted I selected a 2-d bar chart. This created a bar chart layout for me. After tinkering with the chart I was able to make it pleasing to the eye along with being able to be read easily.
The last thing I wanted to find with the population pyramid and data was the dependency ratio. The dependency ratio is calculated by comparing the youth and elderly populations to the working population.
Dependency Ratio:
DR= 100* (p0-14+ p<65)/ p15-64
p0-14= Youth dependency
p<65= Elderly dependency
p15-64= working class
My equation looked like this: 100*(41.2+22)/136.4= 46.3
The dependency ratio measures the pressure on the working class to provide for both the youth and elderly who are dependent. This shows that it's around the normal for a city to have a dependency ratio such as 46.3.
After collecting data for Colorado Springs, I was then asked to get data on the state of Colorado. I did the same steps that I did when collecting and computing data for Colorado Springs. My data looked like this for the state of Colorado.
Once again I calculated the dependency ratio for the state of Colorado. Both Colorado Springs and the state of Colorado were very close to normal for a dependency ratio. My equation for dependency ratio for the state of Colorado looked like this.
DR= 100*(40.2+22.8)/137=45.9
The DR for Colorado Springs was 46.3, While for Colorado was 45.9. These are only separated by 0.4.
The next process I wanted to find dealt with location Quotients. Location quotient measures concentration of an area. It represents the geographical concentration of particular region compared to another geographical area. If the location quotient is a 1, it means that that area has the exact makeup as the average U.S. town, county, or state depending on what area you are looking at. A number more then 1 means it has a higher average, a number lower then 1 means it has a lower average.
To calculate the location quotient I first had to find total population, total pop. 0-14, percent pop. 0-14, total pop. 65+, percent pop. 65+, total hispanic, percent hispanic, total white, and percent white for Colorado Springs, El Paso County, Colorado, and the United States. By finding all of this data on the census website, it would allow for me to calculate location quotients very easily.
Pictured above is a chart I made with all of the data I needed to find to be able to calculate location quotients. Location quotients are based off of the percentage for each category for the United States. To find the LQ for population 0-14, I took the pop. 0-14 of Colorado Springs and dived it by the pop 0-14 of the U.S. This would give me the location quotient. I would then repeat this process for El Paso County and the state of Colorado. I was asked to find the location quotients of pop. 0-14, 65+, Hispanic, and white.
The final process I wanted to look at was the the tertiary and quaternary sectors. I wanted to find the location quotients of these sectors as well for the state of Colorado along with Colorado Springs. The six sectors I wanted to compute location quotient on were: agriculture and forestry, construction, manufacturing, education, information, and public administration. When looking on the census website at Colorado and Colorado Springs, I wanted to looked at the Select Economic Characteristics census. This would give me the percent of the six industries for the state and the city. Once I had the percent for both the state and city, I was able to calculate the location quotient by taking the percent from the city and dividing it by the percent of the states industry. Again a number close to one meant it was the same as the states.
The only industry that was the same as the states was the information industry. Education and public administration were above the average while agriculture and forestry were way below the average. This could be rationalized because there won't be very much forestry going on in a city really.
After looking at the location quotient and comparing Colorado Springs to the state of Colorado, I would advise my investors to go into the public administration industry. I would also advise my investors to going into an industry for young children or hispanic based off of my first findings on location quotients. The population of 65 and greater is to minimal to invest in a business that is worthwhile and thrive and make money. The best bet is the age grouping of 0-14 as it has the highest LQ. One thing I would throw towards my investors would potentially be that rather then just gearing there business towards children 0-14 just in Colorado Springs, test the market our here first then look at expansion. By finding another city with a LQ of the same or greater then Colorado Springs, the company could potentially open another branch if the one in Colorado Springs thrives and makes money.
